# Read data
car_data2 <- read.csv("~/Downloads/car_data2.csv")
# List of numerical features
numeric_features <- c(
'subscription_length', 'vehicle_age', 'customer_age', 'region_density',
'airbags', 'displacement', 'cylinder', 'turning_radius', 'length', 'width',
'gross_weight', 'ncap_rating'
)
# List of categorical features
categorical_features <- c(
'region_code', 'segment', 'model', 'fuel_type', 'max_torque', 'max_power',
'engine_type', 'rear_brakes_type', 'transmission_type', 'steering_type'
)
# List of binary features
binary_features <- c(
'is_esc', 'is_adjustable_steering', 'is_tpms', 'is_parking_sensors',
'is_parking_camera', 'is_front_fog_lights', 'is_rear_window_wiper',
'is_rear_window_washer', 'is_rear_window_defogger', 'is_brake_assist',
'is_power_door_locks', 'is_central_locking', 'is_power_steering',
'is_driver_seat_height_adjustable', 'is_day_night_rear_view_mirror',
'is_ecw', 'is_speed_alert'
)
# Convert binary features from "yes"/"no" to 1/0
car_data2[binary_features] <- lapply(car_data2[binary_features], function(x) ifelse(x == "Yes", 1, ifelse(x == "No", 0, x)))
# Extract numerical features
numeric_data <- car_data2 %>%
select(all_of(numeric_features))
# Extract categorical features
categorical_data <- car_data2 %>%
select(all_of(categorical_features))
# Extract binary features
binary_data <- car_data2 %>%
select(all_of(binary_features))
# Print extracted data
# Check the first few rows to verify changes
head(car_data2)
## policy_id subscription_length vehicle_age customer_age region_code
## 1 POL045360 9.3 1.2 41 C8
## 2 POL016745 8.2 1.8 35 C2
## 3 POL007194 9.5 0.2 44 C8
## 4 POL018146 5.2 0.4 44 C10
## 5 POL049011 10.1 1.0 56 C13
## 6 POL053680 3.1 2.0 36 C7
## region_density segment model fuel_type max_torque max_power
## 1 8794 C2 M4 Diesel 250Nm@2750rpm 113.45bhp@4000rpm
## 2 27003 C1 M9 Diesel 200Nm@1750rpm 97.89bhp@3600rpm
## 3 8794 C2 M4 Diesel 250Nm@2750rpm 113.45bhp@4000rpm
## 4 73430 A M1 CNG 60Nm@3500rpm 40.36bhp@6000rpm
## 5 5410 B2 M5 Diesel 200Nm@3000rpm 88.77bhp@4000rpm
## 6 6112 B2 M7 Petrol 113Nm@4400rpm 88.50bhp@6000rpm
## engine_type airbags is_esc is_adjustable_steering is_tpms
## 1 1.5 L U2 CRDi 6 1 1 1
## 2 i-DTEC 2 0 1 0
## 3 1.5 L U2 CRDi 6 1 1 1
## 4 F8D Petrol Engine 2 0 0 0
## 5 1.5 Turbocharged Revotorq 2 0 1 0
## 6 1.2 L K Series Engine 6 1 1 0
## is_parking_sensors is_parking_camera rear_brakes_type displacement cylinder
## 1 1 1 Disc 1493 4
## 2 1 1 Drum 1498 4
## 3 1 1 Disc 1493 4
## 4 1 0 Drum 796 3
## 5 1 0 Drum 1497 4
## 6 1 1 Drum 1197 4
## transmission_type steering_type turning_radius length width gross_weight
## 1 Automatic Power 5.20 4300 1790 1720
## 2 Manual Electric 4.90 3995 1695 1051
## 3 Automatic Power 5.20 4300 1790 1720
## 4 Manual Power 4.60 3445 1515 1185
## 5 Manual Electric 5.00 3990 1755 1490
## 6 Automatic Electric 4.85 3990 1745 1410
## is_front_fog_lights is_rear_window_wiper is_rear_window_washer
## 1 1 1 1
## 2 1 0 0
## 3 1 1 1
## 4 0 0 0
## 5 0 0 0
## 6 1 1 1
## is_rear_window_defogger is_brake_assist is_power_door_locks
## 1 1 1 1
## 2 1 0 1
## 3 1 1 1
## 4 0 0 0
## 5 0 0 1
## 6 1 1 1
## is_central_locking is_power_steering is_driver_seat_height_adjustable
## 1 1 1 1
## 2 1 1 1
## 3 1 1 1
## 4 0 1 0
## 5 1 1 0
## 6 1 1 1
## is_day_night_rear_view_mirror is_ecw is_speed_alert ncap_rating claim_status
## 1 0 1 1 3 0
## 2 1 1 1 4 0
## 3 0 1 1 3 0
## 4 0 0 1 0 0
## 5 0 1 1 5 0
## 6 1 1 1 0 0
# Read data
car_data2 <- read.csv("~/Downloads/car_data2.csv")
# List of binary features
binary_features <- c(
'is_esc', 'is_adjustable_steering', 'is_tpms', 'is_parking_sensors',
'is_parking_camera', 'is_front_fog_lights', 'is_rear_window_wiper',
'is_rear_window_washer', 'is_rear_window_defogger', 'is_brake_assist',
'is_power_door_locks', 'is_central_locking', 'is_power_steering',
'is_driver_seat_height_adjustable', 'is_day_night_rear_view_mirror',
'is_ecw', 'is_speed_alert'
)
# Convert binary features
car_data2[binary_features] <- lapply(car_data2[binary_features], function(x) ifelse(x == "Yes", 1, ifelse(x == "No", 0, as.numeric(x))))
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
## Warning in ifelse(x == "No", 0, as.numeric(x)): NAs introduced by coercion
# Extract binary features
binary_data <- car_data2 %>%
select(all_of(binary_features))
# Ensure all features are numeric
binary_data <- as.data.frame(lapply(binary_data, as.numeric))
# Perform DBSCAN clustering
set.seed(123)
dbscan_result <- dbscan(binary_data, eps = 0.5, minPts = 5)
# View clustering results
print(dbscan_result)
## DBSCAN clustering for 58592 objects.
## Parameters: eps = 0.5, minPts = 5
## Using euclidean distances and borderpoints = TRUE
## The clustering contains 11 cluster(s) and 0 noise points.
##
## 1 2 3 4 5 6 7 8 9 10 11
## 14018 2114 14948 1598 2940 13776 4173 2373 1080 1209 363
##
## Available fields: cluster, eps, minPts, dist, borderPoints
# Add clustering results to the original data
car_data2$cluster <- dbscan_result$cluster
# Visualize clustering results (using PCA to reduce to 2D for visualization)
binary_data_pca <- prcomp(binary_data, center = TRUE, scale. = TRUE)
pca_data <- data.frame(binary_data_pca$x[,1:2], cluster = as.factor(dbscan_result$cluster))
ggplot(pca_data, aes(x = PC1, y = PC2, color = cluster)) +
geom_point() +
labs(title = "DBSCAN Clustering on Binary Features (PCA Reduced)", x = "Principal Component 1", y = "Principal Component 2")
# Analyze insurance claim rate for each cluster
cluster_claim_analysis <- car_data2 %>%
group_by(cluster) %>%
summarise(
claim_rate = mean(claim_status)
)
print(cluster_claim_analysis)
## # A tibble: 11 × 2
## cluster claim_rate
## <int> <dbl>
## 1 1 0.0643
## 2 2 0.0629
## 3 3 0.0614
## 4 4 0.0726
## 5 5 0.0684
## 6 6 0.0682
## 7 7 0.0585
## 8 8 0.0539
## 9 9 0.0741
## 10 10 0.0604
## 11 11 0.0413
# Analyze feature distribution for each cluster
cluster_summary <- car_data2 %>%
group_by(cluster) %>%
summarise_all(mean, na.rm = TRUE)
## Warning: There were 121 warnings in `summarise()`.
## The first warning was:
## ℹ In argument: `policy_id = (function (x, ...) ...`.
## ℹ In group 1: `cluster = 1`.
## Caused by warning in `mean.default()`:
## ! argument is not numeric or logical: returning NA
## ℹ Run `dplyr::last_dplyr_warnings()` to see the 120 remaining warnings.
print(cluster_summary)
## # A tibble: 11 × 42
## cluster policy_id subscription_length vehicle_age customer_age region_code
## <int> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 NA 6.81 1.78 44.8 NA
## 2 2 NA 6.38 1.45 43.5 NA
## 3 3 NA 4.48 0.512 45.4 NA
## 4 4 NA 6.23 1.73 44.8 NA
## 5 5 NA 6.69 1.69 44.4 NA
## 6 6 NA 6.87 1.72 45.4 NA
## 7 7 NA 6.36 1.47 43.1 NA
## 8 8 NA 6.43 1.52 43.9 NA
## 9 9 NA 6.32 1.68 44.0 NA
## 10 10 NA 5.75 1.54 43.7 NA
## 11 11 NA 6.66 2.06 44.7 NA
## # ℹ 36 more variables: region_density <dbl>, segment <dbl>, model <dbl>,
## # fuel_type <dbl>, max_torque <dbl>, max_power <dbl>, engine_type <dbl>,
## # airbags <dbl>, is_esc <dbl>, is_adjustable_steering <dbl>, is_tpms <dbl>,
## # is_parking_sensors <dbl>, is_parking_camera <dbl>, rear_brakes_type <dbl>,
## # displacement <dbl>, cylinder <dbl>, transmission_type <dbl>,
## # steering_type <dbl>, turning_radius <dbl>, length <dbl>, width <dbl>,
## # gross_weight <dbl>, is_front_fog_lights <dbl>, …
# Use clustering results as the dependent variable and binary features as independent variables
set.seed(123)
rf_model <- randomForest(as.factor(car_data2$claim_status) ~ ., data = binary_data)
# View feature importance
importance <- importance(rf_model)
var_importance <- data.frame(Feature = rownames(importance), Importance = importance[, 1])
# Sort by importance
var_importance <- var_importance[order(-var_importance$Importance), ]
print(var_importance)
## Feature Importance
## is_adjustable_steering is_adjustable_steering 0.65230308
## is_front_fog_lights is_front_fog_lights 0.34067299
## is_brake_assist is_brake_assist 0.26011907
## is_day_night_rear_view_mirror is_day_night_rear_view_mirror 0.22461612
## is_driver_seat_height_adjustable is_driver_seat_height_adjustable 0.22370237
## is_speed_alert is_speed_alert 0.17115382
## is_parking_camera is_parking_camera 0.16774573
## is_parking_sensors is_parking_sensors 0.16030773
## is_esc is_esc 0.09875457
## is_tpms is_tpms 0.09802271
## is_rear_window_defogger is_rear_window_defogger 0.08478399
## is_ecw is_ecw 0.07547211
## is_rear_window_wiper is_rear_window_wiper 0.07038729
## is_rear_window_washer is_rear_window_washer 0.07018289
## is_central_locking is_central_locking 0.06466322
## is_power_door_locks is_power_door_locks 0.05819822
## is_power_steering is_power_steering 0.05251634
# Visualize feature importance
ggplot(var_importance, aes(x = reorder(Feature, Importance), y = Importance)) +
geom_bar(stat = "identity") +
coord_flip() +
labs(title = "Feature Importance for Predicting Insurance Claims", x = "Feature", y = "Importance")
# Read data
car_data2 <- read.csv("~/Downloads/car_data2.csv")
# List of categorical features
categorical_features <- c(
'region_code', 'segment', 'model', 'fuel_type', 'max_torque', 'max_power',
'engine_type', 'rear_brakes_type', 'transmission_type', 'steering_type'
)
# Calculate and display the distribution of each categorical variable
for (feature in categorical_features) {
cat("Data Distribution for:", feature, "\n")
print(table(car_data2[[feature]]))
cat("\n")
}
## Data Distribution for: region_code
##
## C1 C10 C11 C12 C13 C14 C15 C16 C17 C18 C19 C2 C20
## 1468 3155 1212 1589 3423 3660 771 401 492 242 952 7342 109
## C21 C22 C3 C4 C5 C6 C7 C8 C9
## 379 207 6101 665 6979 890 2167 13654 2734
##
## Data Distribution for: segment
##
## A B1 B2 C1 C2 Utility
## 17321 4173 18314 3557 14018 1209
##
## Data Distribution for: model
##
## M1 M10 M11 M2 M3 M4 M5 M6 M7 M8 M9
## 14948 1209 363 1080 2373 14018 1598 13776 2940 4173 2114
##
## Data Distribution for: fuel_type
##
## CNG Diesel Petrol
## 20330 17730 20532
##
## Data Distribution for: max_torque
##
## 113Nm@4400rpm 170Nm@4000rpm 200Nm@1750rpm 200Nm@3000rpm 250Nm@2750rpm
## 17796 363 2114 1598 14018
## 60Nm@3500rpm 82.1Nm@3400rpm 85Nm@3000rpm 91Nm@4250rpm
## 14948 4173 1209 2373
##
## Data Distribution for: max_power
##
## 113.45bhp@4000rpm 118.36bhp@5500rpm 40.36bhp@6000rpm 55.92bhp@5300rpm
## 14018 363 14948 4173
## 61.68bhp@6000rpm 67.06bhp@5500rpm 88.50bhp@6000rpm 88.77bhp@4000rpm
## 1209 2373 17796 1598
## 97.89bhp@3600rpm
## 2114
##
## Data Distribution for: engine_type
##
## 1.0 SCe 1.2 L K Series Engine 1.2 L K12N Dualjet
## 2373 2940 1080
## 1.5 L U2 CRDi 1.5 Turbocharged Revotorq 1.5 Turbocharged Revotron
## 14018 1598 363
## F8D Petrol Engine G12B i-DTEC
## 14948 1209 2114
## K Series Dual jet K10C
## 13776 4173
##
## Data Distribution for: rear_brakes_type
##
## Disc Drum
## 14018 44574
##
## Data Distribution for: transmission_type
##
## Automatic Manual
## 20411 38181
##
## Data Distribution for: steering_type
##
## Electric Manual Power
## 23881 1209 33502
# List of categorical features
categorical_features <- c(
'region_code', 'segment', 'model', 'fuel_type', 'max_torque', 'max_power',
'engine_type', 'rear_brakes_type', 'transmission_type', 'steering_type'
)
# Generate frequency tables and bar plots
for (feature in categorical_features) {
cat("Frequency Distribution for:", feature, "\n")
print(table(car_data2[[feature]]))
cat("\n")
# Plot bar chart
ggplot(car_data2, aes_string(x = feature)) +
geom_bar() +
labs(title = paste("Distribution of", feature), x = feature, y = "Count") +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
theme_minimal()
}
## Frequency Distribution for: region_code
##
## C1 C10 C11 C12 C13 C14 C15 C16 C17 C18 C19 C2 C20
## 1468 3155 1212 1589 3423 3660 771 401 492 242 952 7342 109
## C21 C22 C3 C4 C5 C6 C7 C8 C9
## 379 207 6101 665 6979 890 2167 13654 2734
## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation idioms with `aes()`.
## ℹ See also `vignette("ggplot2-in-packages")` for more information.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Frequency Distribution for: segment
##
## A B1 B2 C1 C2 Utility
## 17321 4173 18314 3557 14018 1209
##
## Frequency Distribution for: model
##
## M1 M10 M11 M2 M3 M4 M5 M6 M7 M8 M9
## 14948 1209 363 1080 2373 14018 1598 13776 2940 4173 2114
##
## Frequency Distribution for: fuel_type
##
## CNG Diesel Petrol
## 20330 17730 20532
##
## Frequency Distribution for: max_torque
##
## 113Nm@4400rpm 170Nm@4000rpm 200Nm@1750rpm 200Nm@3000rpm 250Nm@2750rpm
## 17796 363 2114 1598 14018
## 60Nm@3500rpm 82.1Nm@3400rpm 85Nm@3000rpm 91Nm@4250rpm
## 14948 4173 1209 2373
##
## Frequency Distribution for: max_power
##
## 113.45bhp@4000rpm 118.36bhp@5500rpm 40.36bhp@6000rpm 55.92bhp@5300rpm
## 14018 363 14948 4173
## 61.68bhp@6000rpm 67.06bhp@5500rpm 88.50bhp@6000rpm 88.77bhp@4000rpm
## 1209 2373 17796 1598
## 97.89bhp@3600rpm
## 2114
##
## Frequency Distribution for: engine_type
##
## 1.0 SCe 1.2 L K Series Engine 1.2 L K12N Dualjet
## 2373 2940 1080
## 1.5 L U2 CRDi 1.5 Turbocharged Revotorq 1.5 Turbocharged Revotron
## 14018 1598 363
## F8D Petrol Engine G12B i-DTEC
## 14948 1209 2114
## K Series Dual jet K10C
## 13776 4173
##
## Frequency Distribution for: rear_brakes_type
##
## Disc Drum
## 14018 44574
##
## Frequency Distribution for: transmission_type
##
## Automatic Manual
## 20411 38181
##
## Frequency Distribution for: steering_type
##
## Electric Manual Power
## 23881 1209 33502
# Generate cross-tabulations and stacked bar charts for categorical features with claim_status
for (feature in categorical_features) {
cat("Cross-tabulation with claim_status for:", feature, "\n")
print(table(car_data2[[feature]], car_data2$claim_status))
cat("\n")
# Plot stacked bar chart
ggplot(car_data2, aes_string(x = feature, fill = "factor(claim_status)")) +
geom_bar(position = "fill") +
labs(title = paste("Distribution of", feature, "by Claim Status"), x = feature, y = "Proportion") +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
theme_minimal()
}
## Cross-tabulation with claim_status for: region_code
##
## 0 1
## C1 1392 76
## C10 3007 148
## C11 1140 72
## C12 1502 87
## C13 3228 195
## C14 3379 281
## C15 733 38
## C16 378 23
## C17 473 19
## C18 216 26
## C19 881 71
## C2 6822 520
## C20 104 5
## C21 350 29
## C22 190 17
## C3 5668 433
## C4 614 51
## C5 6576 403
## C6 835 55
## C7 2058 109
## C8 12700 954
## C9 2598 136
##
## Cross-tabulation with claim_status for: segment
##
## 0 1
## A 16275 1046
## B1 3929 244
## B2 17058 1256
## C1 3329 228
## C2 13117 901
## Utility 1136 73
##
## Cross-tabulation with claim_status for: model
##
## 0 1
## M1 14030 918
## M10 1136 73
## M11 348 15
## M2 1000 80
## M3 2245 128
## M4 13117 901
## M5 1482 116
## M6 12837 939
## M7 2739 201
## M8 3929 244
## M9 1981 133
##
## Cross-tabulation with claim_status for: fuel_type
##
## 0 1
## CNG 19095 1235
## Diesel 16580 1150
## Petrol 19169 1363
##
## Cross-tabulation with claim_status for: max_torque
##
## 0 1
## 113Nm@4400rpm 16576 1220
## 170Nm@4000rpm 348 15
## 200Nm@1750rpm 1981 133
## 200Nm@3000rpm 1482 116
## 250Nm@2750rpm 13117 901
## 60Nm@3500rpm 14030 918
## 82.1Nm@3400rpm 3929 244
## 85Nm@3000rpm 1136 73
## 91Nm@4250rpm 2245 128
##
## Cross-tabulation with claim_status for: max_power
##
## 0 1
## 113.45bhp@4000rpm 13117 901
## 118.36bhp@5500rpm 348 15
## 40.36bhp@6000rpm 14030 918
## 55.92bhp@5300rpm 3929 244
## 61.68bhp@6000rpm 1136 73
## 67.06bhp@5500rpm 2245 128
## 88.50bhp@6000rpm 16576 1220
## 88.77bhp@4000rpm 1482 116
## 97.89bhp@3600rpm 1981 133
##
## Cross-tabulation with claim_status for: engine_type
##
## 0 1
## 1.0 SCe 2245 128
## 1.2 L K Series Engine 2739 201
## 1.2 L K12N Dualjet 1000 80
## 1.5 L U2 CRDi 13117 901
## 1.5 Turbocharged Revotorq 1482 116
## 1.5 Turbocharged Revotron 348 15
## F8D Petrol Engine 14030 918
## G12B 1136 73
## i-DTEC 1981 133
## K Series Dual jet 12837 939
## K10C 3929 244
##
## Cross-tabulation with claim_status for: rear_brakes_type
##
## 0 1
## Disc 13117 901
## Drum 41727 2847
##
## Cross-tabulation with claim_status for: transmission_type
##
## 0 1
## Automatic 19101 1310
## Manual 35743 2438
##
## Cross-tabulation with claim_status for: steering_type
##
## 0 1
## Electric 22284 1597
## Manual 1136 73
## Power 31424 2078
# Generate cross-tabulations and heatmaps for pairs of categorical features
library(reshape2)
for (i in 1:(length(categorical_features) - 1)) {
for (j in (i + 1):length(categorical_features)) {
feature1 <- categorical_features[i]
feature2 <- categorical_features[j]
cat("Cross-tabulation between", feature1, "and", feature2, "\n")
crosstab <- table(car_data2[[feature1]], car_data2[[feature2]])
print(crosstab)
cat("\n")
# Plot heatmap
crosstab_melt <- melt(crosstab)
ggplot(crosstab_melt, aes_string(x = "Var1", y = "Var2", fill = "value")) +
geom_tile() +
labs(title = paste("Heatmap of", feature1, "and", feature2), x = feature1, y = feature2) +
scale_fill_gradient(low = "white", high = "blue") +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
theme_minimal()
}
}
## Cross-tabulation between region_code and segment
##
## A B1 B2 C1 C2 Utility
## C1 777 74 305 74 219 19
## C10 1350 177 836 170 564 58
## C11 372 77 457 86 198 22
## C12 321 118 627 113 372 38
## C13 732 248 1181 203 996 63
## C14 477 330 1404 286 1071 92
## C15 225 44 229 60 188 25
## C16 287 29 31 17 32 5
## C17 276 32 107 20 51 6
## C18 179 13 28 3 19 0
## C19 201 64 311 60 288 28
## C2 2017 557 2285 542 1757 184
## C20 59 6 24 6 14 0
## C21 131 32 125 14 72 5
## C22 87 17 62 8 29 4
## C3 3471 336 1036 256 896 106
## C4 295 51 131 48 126 14
## C5 2855 528 1721 431 1308 136
## C6 343 76 255 36 164 16
## C7 742 196 610 116 458 45
## C8 1097 986 5757 820 4699 295
## C9 1027 182 792 188 497 48
##
## Cross-tabulation between region_code and model
##
## M1 M10 M11 M2 M3 M4 M5 M6 M7 M8 M9
## C1 735 19 4 29 42 219 30 229 46 74 41
## C10 1232 58 23 43 118 564 80 618 138 177 104
## C11 317 22 8 14 55 198 26 301 130 77 64
## C12 242 38 8 27 79 372 59 474 94 118 78
## C13 566 63 18 66 166 996 99 895 187 248 119
## C14 329 92 15 93 148 1071 129 1024 251 330 178
## C15 194 25 3 18 31 188 24 164 41 44 39
## C16 280 5 3 4 7 32 0 26 5 29 10
## C17 268 6 1 7 8 51 12 84 11 32 12
## C18 175 0 1 0 4 19 1 22 5 13 2
## C19 164 28 5 25 37 288 38 226 47 64 30
## C2 1599 184 48 181 418 1757 215 1723 347 557 313
## C20 55 0 1 3 4 14 0 17 7 6 2
## C21 121 5 5 4 10 72 11 88 26 32 5
## C22 78 4 0 4 9 29 5 45 12 17 4
## C3 3307 106 39 78 164 896 101 748 187 336 139
## C4 272 14 1 19 23 126 13 94 24 51 28
## C5 2546 136 54 118 309 1308 229 1191 301 528 259
## C6 314 16 1 15 29 164 16 194 45 76 20
## C7 680 45 7 24 62 458 46 461 103 196 85
## C8 562 295 100 251 535 4699 401 4602 754 986 469
## C9 912 48 18 57 115 497 63 550 179 182 113
##
## Cross-tabulation between region_code and fuel_type
##
## CNG Diesel Petrol
## C1 828 290 350
## C10 1467 748 940
## C11 416 288 508
## C12 398 509 682
## C13 877 1214 1332
## C14 751 1378 1531
## C15 263 251 257
## C16 314 42 45
## C17 306 75 111
## C18 188 22 32
## C19 256 356 340
## C2 2340 2285 2717
## C20 61 16 32
## C21 158 88 133
## C22 99 38 70
## C3 3749 1136 1216
## C4 337 167 161
## C5 3210 1796 1973
## C6 406 200 284
## C7 921 589 657
## C8 1843 5569 6242
## C9 1142 673 919
##
## Cross-tabulation between region_code and max_torque
##
## 113Nm@4400rpm 170Nm@4000rpm 200Nm@1750rpm 200Nm@3000rpm 250Nm@2750rpm
## C1 304 4 41 30 219
## C10 799 23 104 80 564
## C11 445 8 64 26 198
## C12 595 8 78 59 372
## C13 1148 18 119 99 996
## C14 1368 15 178 129 1071
## C15 223 3 39 24 188
## C16 35 3 10 0 32
## C17 102 1 12 12 51
## C18 27 1 2 1 19
## C19 298 5 30 38 288
## C2 2251 48 313 215 1757
## C20 27 1 2 0 14
## C21 118 5 5 11 72
## C22 61 0 4 5 29
## C3 1013 39 139 101 896
## C4 137 1 28 13 126
## C5 1610 54 259 229 1308
## C6 254 1 20 16 164
## C7 588 7 85 46 458
## C8 5607 100 469 401 4699
## C9 786 18 113 63 497
##
## 60Nm@3500rpm 82.1Nm@3400rpm 85Nm@3000rpm 91Nm@4250rpm
## C1 735 74 19 42
## C10 1232 177 58 118
## C11 317 77 22 55
## C12 242 118 38 79
## C13 566 248 63 166
## C14 329 330 92 148
## C15 194 44 25 31
## C16 280 29 5 7
## C17 268 32 6 8
## C18 175 13 0 4
## C19 164 64 28 37
## C2 1599 557 184 418
## C20 55 6 0 4
## C21 121 32 5 10
## C22 78 17 4 9
## C3 3307 336 106 164
## C4 272 51 14 23
## C5 2546 528 136 309
## C6 314 76 16 29
## C7 680 196 45 62
## C8 562 986 295 535
## C9 912 182 48 115
##
## Cross-tabulation between region_code and max_power
##
## 113.45bhp@4000rpm 118.36bhp@5500rpm 40.36bhp@6000rpm 55.92bhp@5300rpm
## C1 219 4 735 74
## C10 564 23 1232 177
## C11 198 8 317 77
## C12 372 8 242 118
## C13 996 18 566 248
## C14 1071 15 329 330
## C15 188 3 194 44
## C16 32 3 280 29
## C17 51 1 268 32
## C18 19 1 175 13
## C19 288 5 164 64
## C2 1757 48 1599 557
## C20 14 1 55 6
## C21 72 5 121 32
## C22 29 0 78 17
## C3 896 39 3307 336
## C4 126 1 272 51
## C5 1308 54 2546 528
## C6 164 1 314 76
## C7 458 7 680 196
## C8 4699 100 562 986
## C9 497 18 912 182
##
## 61.68bhp@6000rpm 67.06bhp@5500rpm 88.50bhp@6000rpm 88.77bhp@4000rpm
## C1 19 42 304 30
## C10 58 118 799 80
## C11 22 55 445 26
## C12 38 79 595 59
## C13 63 166 1148 99
## C14 92 148 1368 129
## C15 25 31 223 24
## C16 5 7 35 0
## C17 6 8 102 12
## C18 0 4 27 1
## C19 28 37 298 38
## C2 184 418 2251 215
## C20 0 4 27 0
## C21 5 10 118 11
## C22 4 9 61 5
## C3 106 164 1013 101
## C4 14 23 137 13
## C5 136 309 1610 229
## C6 16 29 254 16
## C7 45 62 588 46
## C8 295 535 5607 401
## C9 48 115 786 63
##
## 97.89bhp@3600rpm
## C1 41
## C10 104
## C11 64
## C12 78
## C13 119
## C14 178
## C15 39
## C16 10
## C17 12
## C18 2
## C19 30
## C2 313
## C20 2
## C21 5
## C22 4
## C3 139
## C4 28
## C5 259
## C6 20
## C7 85
## C8 469
## C9 113
##
## Cross-tabulation between region_code and engine_type
##
## 1.0 SCe 1.2 L K Series Engine 1.2 L K12N Dualjet 1.5 L U2 CRDi
## C1 42 46 29 219
## C10 118 138 43 564
## C11 55 130 14 198
## C12 79 94 27 372
## C13 166 187 66 996
## C14 148 251 93 1071
## C15 31 41 18 188
## C16 7 5 4 32
## C17 8 11 7 51
## C18 4 5 0 19
## C19 37 47 25 288
## C2 418 347 181 1757
## C20 4 7 3 14
## C21 10 26 4 72
## C22 9 12 4 29
## C3 164 187 78 896
## C4 23 24 19 126
## C5 309 301 118 1308
## C6 29 45 15 164
## C7 62 103 24 458
## C8 535 754 251 4699
## C9 115 179 57 497
##
## 1.5 Turbocharged Revotorq 1.5 Turbocharged Revotron F8D Petrol Engine
## C1 30 4 735
## C10 80 23 1232
## C11 26 8 317
## C12 59 8 242
## C13 99 18 566
## C14 129 15 329
## C15 24 3 194
## C16 0 3 280
## C17 12 1 268
## C18 1 1 175
## C19 38 5 164
## C2 215 48 1599
## C20 0 1 55
## C21 11 5 121
## C22 5 0 78
## C3 101 39 3307
## C4 13 1 272
## C5 229 54 2546
## C6 16 1 314
## C7 46 7 680
## C8 401 100 562
## C9 63 18 912
##
## G12B i-DTEC K Series Dual jet K10C
## C1 19 41 229 74
## C10 58 104 618 177
## C11 22 64 301 77
## C12 38 78 474 118
## C13 63 119 895 248
## C14 92 178 1024 330
## C15 25 39 164 44
## C16 5 10 26 29
## C17 6 12 84 32
## C18 0 2 22 13
## C19 28 30 226 64
## C2 184 313 1723 557
## C20 0 2 17 6
## C21 5 5 88 32
## C22 4 4 45 17
## C3 106 139 748 336
## C4 14 28 94 51
## C5 136 259 1191 528
## C6 16 20 194 76
## C7 45 85 461 196
## C8 295 469 4602 986
## C9 48 113 550 182
##
## Cross-tabulation between region_code and rear_brakes_type
##
## Disc Drum
## C1 219 1249
## C10 564 2591
## C11 198 1014
## C12 372 1217
## C13 996 2427
## C14 1071 2589
## C15 188 583
## C16 32 369
## C17 51 441
## C18 19 223
## C19 288 664
## C2 1757 5585
## C20 14 95
## C21 72 307
## C22 29 178
## C3 896 5205
## C4 126 539
## C5 1308 5671
## C6 164 726
## C7 458 1709
## C8 4699 8955
## C9 497 2237
##
## Cross-tabulation between region_code and transmission_type
##
## Automatic Manual
## C1 336 1132
## C10 863 2292
## C11 397 815
## C12 572 1017
## C13 1415 2008
## C14 1563 2097
## C15 278 493
## C16 48 353
## C17 77 415
## C18 28 214
## C19 397 555
## C2 2703 4639
## C20 28 81
## C21 112 267
## C22 54 153
## C3 1325 4776
## C4 192 473
## C5 2036 4943
## C6 253 637
## C7 647 1520
## C8 6239 7415
## C9 848 1886
##
## Cross-tabulation between region_code and steering_type
##
## Electric Manual Power
## C1 417 19 1032
## C10 1101 58 1996
## C11 590 22 600
## C12 811 38 740
## C13 1532 63 1828
## C14 1823 92 1745
## C15 317 25 429
## C16 52 5 344
## C17 134 6 352
## C18 34 0 208
## C19 403 28 521
## C2 3197 184 3961
## C20 33 0 76
## C21 144 5 230
## C22 79 4 124
## C3 1417 106 4578
## C4 201 14 450
## C5 2407 136 4436
## C6 319 16 555
## C7 781 45 1341
## C8 7012 295 6347
## C9 1077 48 1609
##
## Cross-tabulation between segment and model
##
## M1 M10 M11 M2 M3 M4 M5 M6 M7 M8 M9
## A 14948 0 0 0 2373 0 0 0 0 0 0
## B1 0 0 0 0 0 0 0 0 0 4173 0
## B2 0 0 0 0 0 0 1598 13776 2940 0 0
## C1 0 0 363 1080 0 0 0 0 0 0 2114
## C2 0 0 0 0 0 14018 0 0 0 0 0
## Utility 0 1209 0 0 0 0 0 0 0 0 0
##
## Cross-tabulation between segment and fuel_type
##
## CNG Diesel Petrol
## A 14948 0 2373
## B1 4173 0 0
## B2 0 1598 16716
## C1 0 2114 1443
## C2 0 14018 0
## Utility 1209 0 0
##
## Cross-tabulation between segment and max_torque
##
## 113Nm@4400rpm 170Nm@4000rpm 200Nm@1750rpm 200Nm@3000rpm 250Nm@2750rpm
## A 0 0 0 0 0
## B1 0 0 0 0 0
## B2 16716 0 0 1598 0
## C1 1080 363 2114 0 0
## C2 0 0 0 0 14018
## Utility 0 0 0 0 0
##
## 60Nm@3500rpm 82.1Nm@3400rpm 85Nm@3000rpm 91Nm@4250rpm
## A 14948 0 0 2373
## B1 0 4173 0 0
## B2 0 0 0 0
## C1 0 0 0 0
## C2 0 0 0 0
## Utility 0 0 1209 0
##
## Cross-tabulation between segment and max_power
##
## 113.45bhp@4000rpm 118.36bhp@5500rpm 40.36bhp@6000rpm 55.92bhp@5300rpm
## A 0 0 14948 0
## B1 0 0 0 4173
## B2 0 0 0 0
## C1 0 363 0 0
## C2 14018 0 0 0
## Utility 0 0 0 0
##
## 61.68bhp@6000rpm 67.06bhp@5500rpm 88.50bhp@6000rpm 88.77bhp@4000rpm
## A 0 2373 0 0
## B1 0 0 0 0
## B2 0 0 16716 1598
## C1 0 0 1080 0
## C2 0 0 0 0
## Utility 1209 0 0 0
##
## 97.89bhp@3600rpm
## A 0
## B1 0
## B2 0
## C1 2114
## C2 0
## Utility 0
##
## Cross-tabulation between segment and engine_type
##
## 1.0 SCe 1.2 L K Series Engine 1.2 L K12N Dualjet 1.5 L U2 CRDi
## A 2373 0 0 0
## B1 0 0 0 0
## B2 0 2940 0 0
## C1 0 0 1080 0
## C2 0 0 0 14018
## Utility 0 0 0 0
##
## 1.5 Turbocharged Revotorq 1.5 Turbocharged Revotron F8D Petrol Engine
## A 0 0 14948
## B1 0 0 0
## B2 1598 0 0
## C1 0 363 0
## C2 0 0 0
## Utility 0 0 0
##
## G12B i-DTEC K Series Dual jet K10C
## A 0 0 0 0
## B1 0 0 0 4173
## B2 0 0 13776 0
## C1 0 2114 0 0
## C2 0 0 0 0
## Utility 1209 0 0 0
##
## Cross-tabulation between segment and rear_brakes_type
##
## Disc Drum
## A 0 17321
## B1 0 4173
## B2 0 18314
## C1 0 3557
## C2 14018 0
## Utility 0 1209
##
## Cross-tabulation between segment and transmission_type
##
## Automatic Manual
## A 2373 14948
## B1 0 4173
## B2 2940 15374
## C1 1080 2477
## C2 14018 0
## Utility 0 1209
##
## Cross-tabulation between segment and steering_type
##
## Electric Manual Power
## A 2373 0 14948
## B1 0 0 4173
## B2 18314 0 0
## C1 3194 0 363
## C2 0 0 14018
## Utility 0 1209 0
##
## Cross-tabulation between model and fuel_type
##
## CNG Diesel Petrol
## M1 14948 0 0
## M10 1209 0 0
## M11 0 0 363
## M2 0 0 1080
## M3 0 0 2373
## M4 0 14018 0
## M5 0 1598 0
## M6 0 0 13776
## M7 0 0 2940
## M8 4173 0 0
## M9 0 2114 0
##
## Cross-tabulation between model and max_torque
##
## 113Nm@4400rpm 170Nm@4000rpm 200Nm@1750rpm 200Nm@3000rpm 250Nm@2750rpm
## M1 0 0 0 0 0
## M10 0 0 0 0 0
## M11 0 363 0 0 0
## M2 1080 0 0 0 0
## M3 0 0 0 0 0
## M4 0 0 0 0 14018
## M5 0 0 0 1598 0
## M6 13776 0 0 0 0
## M7 2940 0 0 0 0
## M8 0 0 0 0 0
## M9 0 0 2114 0 0
##
## 60Nm@3500rpm 82.1Nm@3400rpm 85Nm@3000rpm 91Nm@4250rpm
## M1 14948 0 0 0
## M10 0 0 1209 0
## M11 0 0 0 0
## M2 0 0 0 0
## M3 0 0 0 2373
## M4 0 0 0 0
## M5 0 0 0 0
## M6 0 0 0 0
## M7 0 0 0 0
## M8 0 4173 0 0
## M9 0 0 0 0
##
## Cross-tabulation between model and max_power
##
## 113.45bhp@4000rpm 118.36bhp@5500rpm 40.36bhp@6000rpm 55.92bhp@5300rpm
## M1 0 0 14948 0
## M10 0 0 0 0
## M11 0 363 0 0
## M2 0 0 0 0
## M3 0 0 0 0
## M4 14018 0 0 0
## M5 0 0 0 0
## M6 0 0 0 0
## M7 0 0 0 0
## M8 0 0 0 4173
## M9 0 0 0 0
##
## 61.68bhp@6000rpm 67.06bhp@5500rpm 88.50bhp@6000rpm 88.77bhp@4000rpm
## M1 0 0 0 0
## M10 1209 0 0 0
## M11 0 0 0 0
## M2 0 0 1080 0
## M3 0 2373 0 0
## M4 0 0 0 0
## M5 0 0 0 1598
## M6 0 0 13776 0
## M7 0 0 2940 0
## M8 0 0 0 0
## M9 0 0 0 0
##
## 97.89bhp@3600rpm
## M1 0
## M10 0
## M11 0
## M2 0
## M3 0
## M4 0
## M5 0
## M6 0
## M7 0
## M8 0
## M9 2114
##
## Cross-tabulation between model and engine_type
##
## 1.0 SCe 1.2 L K Series Engine 1.2 L K12N Dualjet 1.5 L U2 CRDi
## M1 0 0 0 0
## M10 0 0 0 0
## M11 0 0 0 0
## M2 0 0 1080 0
## M3 2373 0 0 0
## M4 0 0 0 14018
## M5 0 0 0 0
## M6 0 0 0 0
## M7 0 2940 0 0
## M8 0 0 0 0
## M9 0 0 0 0
##
## 1.5 Turbocharged Revotorq 1.5 Turbocharged Revotron F8D Petrol Engine
## M1 0 0 14948
## M10 0 0 0
## M11 0 363 0
## M2 0 0 0
## M3 0 0 0
## M4 0 0 0
## M5 1598 0 0
## M6 0 0 0
## M7 0 0 0
## M8 0 0 0
## M9 0 0 0
##
## G12B i-DTEC K Series Dual jet K10C
## M1 0 0 0 0
## M10 1209 0 0 0
## M11 0 0 0 0
## M2 0 0 0 0
## M3 0 0 0 0
## M4 0 0 0 0
## M5 0 0 0 0
## M6 0 0 13776 0
## M7 0 0 0 0
## M8 0 0 0 4173
## M9 0 2114 0 0
##
## Cross-tabulation between model and rear_brakes_type
##
## Disc Drum
## M1 0 14948
## M10 0 1209
## M11 0 363
## M2 0 1080
## M3 0 2373
## M4 14018 0
## M5 0 1598
## M6 0 13776
## M7 0 2940
## M8 0 4173
## M9 0 2114
##
## Cross-tabulation between model and transmission_type
##
## Automatic Manual
## M1 0 14948
## M10 0 1209
## M11 0 363
## M2 1080 0
## M3 2373 0
## M4 14018 0
## M5 0 1598
## M6 0 13776
## M7 2940 0
## M8 0 4173
## M9 0 2114
##
## Cross-tabulation between model and steering_type
##
## Electric Manual Power
## M1 0 0 14948
## M10 0 1209 0
## M11 0 0 363
## M2 1080 0 0
## M3 2373 0 0
## M4 0 0 14018
## M5 1598 0 0
## M6 13776 0 0
## M7 2940 0 0
## M8 0 0 4173
## M9 2114 0 0
##
## Cross-tabulation between fuel_type and max_torque
##
## 113Nm@4400rpm 170Nm@4000rpm 200Nm@1750rpm 200Nm@3000rpm 250Nm@2750rpm
## CNG 0 0 0 0 0
## Diesel 0 0 2114 1598 14018
## Petrol 17796 363 0 0 0
##
## 60Nm@3500rpm 82.1Nm@3400rpm 85Nm@3000rpm 91Nm@4250rpm
## CNG 14948 4173 1209 0
## Diesel 0 0 0 0
## Petrol 0 0 0 2373
##
## Cross-tabulation between fuel_type and max_power
##
## 113.45bhp@4000rpm 118.36bhp@5500rpm 40.36bhp@6000rpm 55.92bhp@5300rpm
## CNG 0 0 14948 4173
## Diesel 14018 0 0 0
## Petrol 0 363 0 0
##
## 61.68bhp@6000rpm 67.06bhp@5500rpm 88.50bhp@6000rpm 88.77bhp@4000rpm
## CNG 1209 0 0 0
## Diesel 0 0 0 1598
## Petrol 0 2373 17796 0
##
## 97.89bhp@3600rpm
## CNG 0
## Diesel 2114
## Petrol 0
##
## Cross-tabulation between fuel_type and engine_type
##
## 1.0 SCe 1.2 L K Series Engine 1.2 L K12N Dualjet 1.5 L U2 CRDi
## CNG 0 0 0 0
## Diesel 0 0 0 14018
## Petrol 2373 2940 1080 0
##
## 1.5 Turbocharged Revotorq 1.5 Turbocharged Revotron F8D Petrol Engine
## CNG 0 0 14948
## Diesel 1598 0 0
## Petrol 0 363 0
##
## G12B i-DTEC K Series Dual jet K10C
## CNG 1209 0 0 4173
## Diesel 0 2114 0 0
## Petrol 0 0 13776 0
##
## Cross-tabulation between fuel_type and rear_brakes_type
##
## Disc Drum
## CNG 0 20330
## Diesel 14018 3712
## Petrol 0 20532
##
## Cross-tabulation between fuel_type and transmission_type
##
## Automatic Manual
## CNG 0 20330
## Diesel 14018 3712
## Petrol 6393 14139
##
## Cross-tabulation between fuel_type and steering_type
##
## Electric Manual Power
## CNG 0 1209 19121
## Diesel 3712 0 14018
## Petrol 20169 0 363
##
## Cross-tabulation between max_torque and max_power
##
## 113.45bhp@4000rpm 118.36bhp@5500rpm 40.36bhp@6000rpm
## 113Nm@4400rpm 0 0 0
## 170Nm@4000rpm 0 363 0
## 200Nm@1750rpm 0 0 0
## 200Nm@3000rpm 0 0 0
## 250Nm@2750rpm 14018 0 0
## 60Nm@3500rpm 0 0 14948
## 82.1Nm@3400rpm 0 0 0
## 85Nm@3000rpm 0 0 0
## 91Nm@4250rpm 0 0 0
##
## 55.92bhp@5300rpm 61.68bhp@6000rpm 67.06bhp@5500rpm
## 113Nm@4400rpm 0 0 0
## 170Nm@4000rpm 0 0 0
## 200Nm@1750rpm 0 0 0
## 200Nm@3000rpm 0 0 0
## 250Nm@2750rpm 0 0 0
## 60Nm@3500rpm 0 0 0
## 82.1Nm@3400rpm 4173 0 0
## 85Nm@3000rpm 0 1209 0
## 91Nm@4250rpm 0 0 2373
##
## 88.50bhp@6000rpm 88.77bhp@4000rpm 97.89bhp@3600rpm
## 113Nm@4400rpm 17796 0 0
## 170Nm@4000rpm 0 0 0
## 200Nm@1750rpm 0 0 2114
## 200Nm@3000rpm 0 1598 0
## 250Nm@2750rpm 0 0 0
## 60Nm@3500rpm 0 0 0
## 82.1Nm@3400rpm 0 0 0
## 85Nm@3000rpm 0 0 0
## 91Nm@4250rpm 0 0 0
##
## Cross-tabulation between max_torque and engine_type
##
## 1.0 SCe 1.2 L K Series Engine 1.2 L K12N Dualjet 1.5 L U2 CRDi
## 113Nm@4400rpm 0 2940 1080 0
## 170Nm@4000rpm 0 0 0 0
## 200Nm@1750rpm 0 0 0 0
## 200Nm@3000rpm 0 0 0 0
## 250Nm@2750rpm 0 0 0 14018
## 60Nm@3500rpm 0 0 0 0
## 82.1Nm@3400rpm 0 0 0 0
## 85Nm@3000rpm 0 0 0 0
## 91Nm@4250rpm 2373 0 0 0
##
## 1.5 Turbocharged Revotorq 1.5 Turbocharged Revotron
## 113Nm@4400rpm 0 0
## 170Nm@4000rpm 0 363
## 200Nm@1750rpm 0 0
## 200Nm@3000rpm 1598 0
## 250Nm@2750rpm 0 0
## 60Nm@3500rpm 0 0
## 82.1Nm@3400rpm 0 0
## 85Nm@3000rpm 0 0
## 91Nm@4250rpm 0 0
##
## F8D Petrol Engine G12B i-DTEC K Series Dual jet K10C
## 113Nm@4400rpm 0 0 0 13776 0
## 170Nm@4000rpm 0 0 0 0 0
## 200Nm@1750rpm 0 0 2114 0 0
## 200Nm@3000rpm 0 0 0 0 0
## 250Nm@2750rpm 0 0 0 0 0
## 60Nm@3500rpm 14948 0 0 0 0
## 82.1Nm@3400rpm 0 0 0 0 4173
## 85Nm@3000rpm 0 1209 0 0 0
## 91Nm@4250rpm 0 0 0 0 0
##
## Cross-tabulation between max_torque and rear_brakes_type
##
## Disc Drum
## 113Nm@4400rpm 0 17796
## 170Nm@4000rpm 0 363
## 200Nm@1750rpm 0 2114
## 200Nm@3000rpm 0 1598
## 250Nm@2750rpm 14018 0
## 60Nm@3500rpm 0 14948
## 82.1Nm@3400rpm 0 4173
## 85Nm@3000rpm 0 1209
## 91Nm@4250rpm 0 2373
##
## Cross-tabulation between max_torque and transmission_type
##
## Automatic Manual
## 113Nm@4400rpm 4020 13776
## 170Nm@4000rpm 0 363
## 200Nm@1750rpm 0 2114
## 200Nm@3000rpm 0 1598
## 250Nm@2750rpm 14018 0
## 60Nm@3500rpm 0 14948
## 82.1Nm@3400rpm 0 4173
## 85Nm@3000rpm 0 1209
## 91Nm@4250rpm 2373 0
##
## Cross-tabulation between max_torque and steering_type
##
## Electric Manual Power
## 113Nm@4400rpm 17796 0 0
## 170Nm@4000rpm 0 0 363
## 200Nm@1750rpm 2114 0 0
## 200Nm@3000rpm 1598 0 0
## 250Nm@2750rpm 0 0 14018
## 60Nm@3500rpm 0 0 14948
## 82.1Nm@3400rpm 0 0 4173
## 85Nm@3000rpm 0 1209 0
## 91Nm@4250rpm 2373 0 0
##
## Cross-tabulation between max_power and engine_type
##
## 1.0 SCe 1.2 L K Series Engine 1.2 L K12N Dualjet
## 113.45bhp@4000rpm 0 0 0
## 118.36bhp@5500rpm 0 0 0
## 40.36bhp@6000rpm 0 0 0
## 55.92bhp@5300rpm 0 0 0
## 61.68bhp@6000rpm 0 0 0
## 67.06bhp@5500rpm 2373 0 0
## 88.50bhp@6000rpm 0 2940 1080
## 88.77bhp@4000rpm 0 0 0
## 97.89bhp@3600rpm 0 0 0
##
## 1.5 L U2 CRDi 1.5 Turbocharged Revotorq
## 113.45bhp@4000rpm 14018 0
## 118.36bhp@5500rpm 0 0
## 40.36bhp@6000rpm 0 0
## 55.92bhp@5300rpm 0 0
## 61.68bhp@6000rpm 0 0
## 67.06bhp@5500rpm 0 0
## 88.50bhp@6000rpm 0 0
## 88.77bhp@4000rpm 0 1598
## 97.89bhp@3600rpm 0 0
##
## 1.5 Turbocharged Revotron F8D Petrol Engine G12B i-DTEC
## 113.45bhp@4000rpm 0 0 0 0
## 118.36bhp@5500rpm 363 0 0 0
## 40.36bhp@6000rpm 0 14948 0 0
## 55.92bhp@5300rpm 0 0 0 0
## 61.68bhp@6000rpm 0 0 1209 0
## 67.06bhp@5500rpm 0 0 0 0
## 88.50bhp@6000rpm 0 0 0 0
## 88.77bhp@4000rpm 0 0 0 0
## 97.89bhp@3600rpm 0 0 0 2114
##
## K Series Dual jet K10C
## 113.45bhp@4000rpm 0 0
## 118.36bhp@5500rpm 0 0
## 40.36bhp@6000rpm 0 0
## 55.92bhp@5300rpm 0 4173
## 61.68bhp@6000rpm 0 0
## 67.06bhp@5500rpm 0 0
## 88.50bhp@6000rpm 13776 0
## 88.77bhp@4000rpm 0 0
## 97.89bhp@3600rpm 0 0
##
## Cross-tabulation between max_power and rear_brakes_type
##
## Disc Drum
## 113.45bhp@4000rpm 14018 0
## 118.36bhp@5500rpm 0 363
## 40.36bhp@6000rpm 0 14948
## 55.92bhp@5300rpm 0 4173
## 61.68bhp@6000rpm 0 1209
## 67.06bhp@5500rpm 0 2373
## 88.50bhp@6000rpm 0 17796
## 88.77bhp@4000rpm 0 1598
## 97.89bhp@3600rpm 0 2114
##
## Cross-tabulation between max_power and transmission_type
##
## Automatic Manual
## 113.45bhp@4000rpm 14018 0
## 118.36bhp@5500rpm 0 363
## 40.36bhp@6000rpm 0 14948
## 55.92bhp@5300rpm 0 4173
## 61.68bhp@6000rpm 0 1209
## 67.06bhp@5500rpm 2373 0
## 88.50bhp@6000rpm 4020 13776
## 88.77bhp@4000rpm 0 1598
## 97.89bhp@3600rpm 0 2114
##
## Cross-tabulation between max_power and steering_type
##
## Electric Manual Power
## 113.45bhp@4000rpm 0 0 14018
## 118.36bhp@5500rpm 0 0 363
## 40.36bhp@6000rpm 0 0 14948
## 55.92bhp@5300rpm 0 0 4173
## 61.68bhp@6000rpm 0 1209 0
## 67.06bhp@5500rpm 2373 0 0
## 88.50bhp@6000rpm 17796 0 0
## 88.77bhp@4000rpm 1598 0 0
## 97.89bhp@3600rpm 2114 0 0
##
## Cross-tabulation between engine_type and rear_brakes_type
##
## Disc Drum
## 1.0 SCe 0 2373
## 1.2 L K Series Engine 0 2940
## 1.2 L K12N Dualjet 0 1080
## 1.5 L U2 CRDi 14018 0
## 1.5 Turbocharged Revotorq 0 1598
## 1.5 Turbocharged Revotron 0 363
## F8D Petrol Engine 0 14948
## G12B 0 1209
## i-DTEC 0 2114
## K Series Dual jet 0 13776
## K10C 0 4173
##
## Cross-tabulation between engine_type and transmission_type
##
## Automatic Manual
## 1.0 SCe 2373 0
## 1.2 L K Series Engine 2940 0
## 1.2 L K12N Dualjet 1080 0
## 1.5 L U2 CRDi 14018 0
## 1.5 Turbocharged Revotorq 0 1598
## 1.5 Turbocharged Revotron 0 363
## F8D Petrol Engine 0 14948
## G12B 0 1209
## i-DTEC 0 2114
## K Series Dual jet 0 13776
## K10C 0 4173
##
## Cross-tabulation between engine_type and steering_type
##
## Electric Manual Power
## 1.0 SCe 2373 0 0
## 1.2 L K Series Engine 2940 0 0
## 1.2 L K12N Dualjet 1080 0 0
## 1.5 L U2 CRDi 0 0 14018
## 1.5 Turbocharged Revotorq 1598 0 0
## 1.5 Turbocharged Revotron 0 0 363
## F8D Petrol Engine 0 0 14948
## G12B 0 1209 0
## i-DTEC 2114 0 0
## K Series Dual jet 13776 0 0
## K10C 0 0 4173
##
## Cross-tabulation between rear_brakes_type and transmission_type
##
## Automatic Manual
## Disc 14018 0
## Drum 6393 38181
##
## Cross-tabulation between rear_brakes_type and steering_type
##
## Electric Manual Power
## Disc 0 0 14018
## Drum 23881 1209 19484
##
## Cross-tabulation between transmission_type and steering_type
##
## Electric Manual Power
## Automatic 6393 0 14018
## Manual 17488 1209 19484
# Perform chi-squared tests of independence for pairs of categorical features
for (i in 1:(length(categorical_features) - 1)) {
for (j in (i + 1):length(categorical_features)) {
feature1 <- categorical_features[i]
feature2 <- categorical_features[j]
cat("Chi-squared test between", feature1, "and", feature2, "\n")
crosstab <- table(car_data2[[feature1]], car_data2[[feature2]])
chi_test <- chisq.test(crosstab)
print(chi_test)
cat("\n")
}
}
## Chi-squared test between region_code and segment
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 8602.2, df = 105, p-value < 2.2e-16
##
##
## Chi-squared test between region_code and model
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 10283, df = 210, p-value < 2.2e-16
##
##
## Chi-squared test between region_code and fuel_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 7170.5, df = 42, p-value < 2.2e-16
##
##
## Chi-squared test between region_code and max_torque
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 10021, df = 168, p-value < 2.2e-16
##
##
## Chi-squared test between region_code and max_power
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 10021, df = 168, p-value < 2.2e-16
##
##
## Chi-squared test between region_code and engine_type
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 10283, df = 210, p-value < 2.2e-16
##
##
## Chi-squared test between region_code and rear_brakes_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 1757, df = 21, p-value < 2.2e-16
##
##
## Chi-squared test between region_code and transmission_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 1953.3, df = 21, p-value < 2.2e-16
##
##
## Chi-squared test between region_code and steering_type
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 2364.3, df = 42, p-value < 2.2e-16
##
##
## Chi-squared test between segment and model
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 292960, df = 50, p-value < 2.2e-16
##
##
## Chi-squared test between segment and fuel_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 91174, df = 10, p-value < 2.2e-16
##
##
## Chi-squared test between segment and max_torque
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 273004, df = 40, p-value < 2.2e-16
##
##
## Chi-squared test between segment and max_power
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 273004, df = 40, p-value < 2.2e-16
##
##
## Chi-squared test between segment and engine_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 292960, df = 50, p-value < 2.2e-16
##
##
## Chi-squared test between segment and rear_brakes_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 58592, df = 5, p-value < 2.2e-16
##
##
## Chi-squared test between segment and transmission_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 35385, df = 5, p-value < 2.2e-16
##
##
## Chi-squared test between segment and steering_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 107208, df = 10, p-value < 2.2e-16
##
##
## Chi-squared test between model and fuel_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 117184, df = 20, p-value < 2.2e-16
##
##
## Chi-squared test between model and max_torque
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 468736, df = 80, p-value < 2.2e-16
##
##
## Chi-squared test between model and max_power
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 468736, df = 80, p-value < 2.2e-16
##
##
## Chi-squared test between model and engine_type
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 585920, df = 100, p-value < 2.2e-16
##
##
## Chi-squared test between model and rear_brakes_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 58592, df = 10, p-value < 2.2e-16
##
##
## Chi-squared test between model and transmission_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 58592, df = 10, p-value < 2.2e-16
##
##
## Chi-squared test between model and steering_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 117184, df = 20, p-value < 2.2e-16
##
##
## Chi-squared test between fuel_type and max_torque
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 117184, df = 16, p-value < 2.2e-16
##
##
## Chi-squared test between fuel_type and max_power
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 117184, df = 16, p-value < 2.2e-16
##
##
## Chi-squared test between fuel_type and engine_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 117184, df = 20, p-value < 2.2e-16
##
##
## Chi-squared test between fuel_type and rear_brakes_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 42467, df = 2, p-value < 2.2e-16
##
##
## Chi-squared test between fuel_type and transmission_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 26270, df = 2, p-value < 2.2e-16
##
##
## Chi-squared test between fuel_type and steering_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 46256, df = 4, p-value < 2.2e-16
##
##
## Chi-squared test between max_torque and max_power
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 468736, df = 64, p-value < 2.2e-16
##
##
## Chi-squared test between max_torque and engine_type
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 468736, df = 80, p-value < 2.2e-16
##
##
## Chi-squared test between max_torque and rear_brakes_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 58592, df = 8, p-value < 2.2e-16
##
##
## Chi-squared test between max_torque and transmission_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 44883, df = 8, p-value < 2.2e-16
##
##
## Chi-squared test between max_torque and steering_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 117184, df = 16, p-value < 2.2e-16
##
##
## Chi-squared test between max_power and engine_type
## Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 468736, df = 80, p-value < 2.2e-16
##
##
## Chi-squared test between max_power and rear_brakes_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 58592, df = 8, p-value < 2.2e-16
##
##
## Chi-squared test between max_power and transmission_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 44883, df = 8, p-value < 2.2e-16
##
##
## Chi-squared test between max_power and steering_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 117184, df = 16, p-value < 2.2e-16
##
##
## Chi-squared test between engine_type and rear_brakes_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 58592, df = 10, p-value < 2.2e-16
##
##
## Chi-squared test between engine_type and transmission_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 58592, df = 10, p-value < 2.2e-16
##
##
## Chi-squared test between engine_type and steering_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 117184, df = 20, p-value < 2.2e-16
##
##
## Chi-squared test between rear_brakes_type and transmission_type
##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: crosstab
## X-squared = 34465, df = 1, p-value < 2.2e-16
##
##
## Chi-squared test between rear_brakes_type and steering_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 13800, df = 2, p-value < 2.2e-16
##
##
## Chi-squared test between transmission_type and steering_type
##
## Pearson's Chi-squared test
##
## data: crosstab
## X-squared = 2055.2, df = 2, p-value < 2.2e-16
# Perform MCA
mca_result <- MCA(categorical_data, graph = TRUE)
# View MCA results
print(mca_result)
## **Results of the Multiple Correspondence Analysis (MCA)**
## The analysis was performed on 58592 individuals, described by 10 variables
## *The results are available in the following objects:
##
## name description
## 1 "$eig" "eigenvalues"
## 2 "$var" "results for the variables"
## 3 "$var$coord" "coord. of the categories"
## 4 "$var$cos2" "cos2 for the categories"
## 5 "$var$contrib" "contributions of the categories"
## 6 "$var$v.test" "v-test for the categories"
## 7 "$var$eta2" "coord. of variables"
## 8 "$ind" "results for the individuals"
## 9 "$ind$coord" "coord. for the individuals"
## 10 "$ind$cos2" "cos2 for the individuals"
## 11 "$ind$contrib" "contributions of the individuals"
## 12 "$call" "intermediate results"
## 13 "$call$marge.col" "weights of columns"
## 14 "$call$marge.li" "weights of rows"
# View feature contributions to the first two principal components
contrib_vars <- mca_result$var$contrib
print(contrib_vars)
## Dim 1 Dim 2 Dim 3 Dim 4
## region_code_C1 1.188873e-02 7.661143e-02 2.366554e-02 5.436293e-02
## region_code_C10 1.275482e-02 4.651231e-02 1.201799e-02 4.266289e-02
## region_code_C11 1.041297e-02 2.862117e-03 2.042383e-04 5.523411e-04
## region_code_C12 4.784609e-04 2.437039e-02 4.563473e-03 7.433830e-03
## region_code_C13 1.101111e-02 2.853344e-02 2.740553e-03 8.916790e-03
## region_code_C14 1.082813e-02 8.822158e-02 2.507143e-02 8.099615e-02
## region_code_C15 5.759683e-05 6.058353e-06 2.494325e-03 6.556688e-04
## region_code_C16 9.597290e-03 9.172856e-02 1.962595e-02 2.626374e-02
## region_code_C17 1.063227e-02 3.752635e-02 1.165774e-02 1.496662e-02
## region_code_C18 6.244261e-03 5.071599e-02 1.841529e-02 2.433026e-02
## region_code_C19 4.969260e-03 3.976651e-03 5.428629e-03 1.569952e-03
## region_code_C2 7.832413e-06 5.796309e-03 6.343240e-03 3.842531e-03
## region_code_C20 1.439984e-03 4.431466e-03 3.806086e-03 4.038373e-03
## region_code_C21 1.373613e-03 1.113419e-03 1.509013e-03 4.859739e-08
## region_code_C22 2.789883e-03 2.590044e-03 8.427473e-04 6.277121e-04
## region_code_C3 4.731777e-02 5.352446e-01 9.976066e-02 2.637670e-01
## region_code_C4 1.027476e-03 2.227350e-02 2.747249e-03 4.018844e-03
## region_code_C5 1.525562e-02 1.095842e-01 2.081670e-02 2.395656e-02
## region_code_C6 3.611790e-03 9.637010e-03 2.939544e-03 5.455501e-04
## region_code_C7 1.796318e-03 1.526114e-02 1.959029e-03 7.025380e-04
## region_code_C8 1.442865e-01 6.875951e-01 1.264998e-01 2.463113e-01
## region_code_C9 1.005325e-02 1.005755e-02 5.699026e-03 9.455579e-03
## segment_A 7.248716e-01 4.267364e+00 1.432615e+00 4.584262e+00
## segment_B1 1.600224e-01 1.550875e+00 3.365354e-01 1.504551e+01
## segment_B2 2.106232e+00 5.503671e+00 3.146306e-02 2.024830e-02
## segment_C1 6.807391e-02 5.370773e-01 5.100960e-03 8.138721e-02
## segment_C2 9.602995e+00 5.843873e-02 7.815939e-02 3.314534e-04
## segment_Utility 2.402779e-01 1.162525e+00 1.477136e+01 6.946031e-03
## M1 6.733230e-01 5.682184e+00 1.502397e+00 3.734041e+00
## M10 2.402779e-01 1.162525e+00 1.477136e+01 6.946031e-03
## M11 1.571259e-02 1.067648e-02 1.665963e-03 8.913886e-03
## M2 4.860919e-02 3.566734e-01 2.994448e-03 8.976997e-04
## M3 5.795993e-02 1.613408e-01 2.476670e-02 8.736508e-01
## M4 9.602995e+00 5.843873e-02 7.815939e-02 3.314534e-04
## M5 3.211897e-02 2.453609e-01 4.384900e-03 1.767485e-02
## M6 2.005677e+00 4.212576e+00 1.933275e-02 1.563809e-02
## M7 1.801491e-01 1.096613e+00 8.632541e-03 1.838568e-04
## M8 1.600224e-01 1.550875e+00 3.365354e-01 1.504551e+01
## M9 1.661765e-02 2.312994e-01 4.962414e-03 9.580110e-02
## CNG 1.008794e+00 8.243476e+00 1.418348e-01 6.410743e-03
## Diesel 7.060340e+00 2.806111e-01 8.572709e-02 1.705670e-02
## Petrol 2.160132e+00 5.591952e+00 1.054147e-02 4.041518e-02
## 113Nm@4400rpm 2.169335e+00 5.657646e+00 3.012965e-02 1.252048e-02
## 170Nm@4000rpm 1.571259e-02 1.067648e-02 1.665963e-03 8.913886e-03
## 200Nm@1750rpm 1.661765e-02 2.312994e-01 4.962414e-03 9.580110e-02
## 200Nm@3000rpm 3.211897e-02 2.453609e-01 4.384900e-03 1.767485e-02
## 250Nm@2750rpm 9.602995e+00 5.843873e-02 7.815939e-02 3.314534e-04
## 60Nm@3500rpm 6.733230e-01 5.682184e+00 1.502397e+00 3.734041e+00
## 82.1Nm@3400rpm 1.600224e-01 1.550875e+00 3.365354e-01 1.504551e+01
## 85Nm@3000rpm 2.402779e-01 1.162525e+00 1.477136e+01 6.946031e-03
## 91Nm@4250rpm 5.795993e-02 1.613408e-01 2.476670e-02 8.736508e-01
## 113.45bhp@4000rpm 9.602995e+00 5.843873e-02 7.815939e-02 3.314534e-04
## 118.36bhp@5500rpm 1.571259e-02 1.067648e-02 1.665963e-03 8.913886e-03
## 40.36bhp@6000rpm 6.733230e-01 5.682184e+00 1.502397e+00 3.734041e+00
## 55.92bhp@5300rpm 1.600224e-01 1.550875e+00 3.365354e-01 1.504551e+01
## 61.68bhp@6000rpm 2.402779e-01 1.162525e+00 1.477136e+01 6.946031e-03
## 67.06bhp@5500rpm 5.795993e-02 1.613408e-01 2.476670e-02 8.736508e-01
## 88.50bhp@6000rpm 2.169335e+00 5.657646e+00 3.012965e-02 1.252048e-02
## 88.77bhp@4000rpm 3.211897e-02 2.453609e-01 4.384900e-03 1.767485e-02
## 97.89bhp@3600rpm 1.661765e-02 2.312994e-01 4.962414e-03 9.580110e-02
## 1.0 SCe 5.795993e-02 1.613408e-01 2.476670e-02 8.736508e-01
## 1.2 L K Series Engine 1.801491e-01 1.096613e+00 8.632541e-03 1.838568e-04
## 1.2 L K12N Dualjet 4.860919e-02 3.566734e-01 2.994448e-03 8.976997e-04
## 1.5 L U2 CRDi 9.602995e+00 5.843873e-02 7.815939e-02 3.314534e-04
## 1.5 Turbocharged Revotorq 3.211897e-02 2.453609e-01 4.384900e-03 1.767485e-02
## 1.5 Turbocharged Revotron 1.571259e-02 1.067648e-02 1.665963e-03 8.913886e-03
## F8D Petrol Engine 6.733230e-01 5.682184e+00 1.502397e+00 3.734041e+00
## G12B 2.402779e-01 1.162525e+00 1.477136e+01 6.946031e-03
## i-DTEC 1.661765e-02 2.312994e-01 4.962414e-03 9.580110e-02
## K Series Dual jet 2.005677e+00 4.212576e+00 1.933275e-02 1.563809e-02
## K10C 1.600224e-01 1.550875e+00 3.365354e-01 1.504551e+01
## Disc 9.602995e+00 5.843873e-02 7.815939e-02 3.314534e-04
## Drum 3.020029e+00 1.837829e-02 2.458021e-02 1.042382e-04
## transmission_type_Automatic 5.172096e+00 7.605753e-01 5.102026e-02 1.102535e-01
## transmission_type_Manual 2.764926e+00 4.065924e-01 2.727468e-02 5.893991e-02
## steering_type_Electric 2.050771e+00 6.008113e+00 1.913280e-02 5.121770e-03
## steering_type_Manual 2.402779e-01 1.162525e+00 1.477136e+01 6.946031e-03
## steering_type_Power 1.695680e+00 3.476922e+00 7.172272e-01 5.814853e-03
## Dim 5
## region_code_C1 6.323202e-04
## region_code_C10 1.178740e-03
## region_code_C11 1.499562e-03
## region_code_C12 2.958907e-04
## region_code_C13 2.664317e-03
## region_code_C14 2.173711e-04
## region_code_C15 2.554725e-03
## region_code_C16 1.481699e-03
## region_code_C17 5.227576e-05
## region_code_C18 7.197287e-05
## region_code_C19 3.367623e-04
## region_code_C2 3.165051e-03
## region_code_C20 1.516214e-05
## region_code_C21 1.513819e-03
## region_code_C22 8.472941e-04
## region_code_C3 2.245060e-03
## region_code_C4 2.326016e-03
## region_code_C5 1.031931e-02
## region_code_C6 2.397191e-03
## region_code_C7 2.109112e-04
## region_code_C8 4.075140e-02
## region_code_C9 3.085073e-03
## segment_A 1.600214e-02
## segment_B1 1.846254e-01
## segment_B2 1.053003e+00
## segment_C1 1.455306e+01
## segment_C2 1.265729e-01
## segment_Utility 3.726538e-03
## M1 3.627505e-03
## M10 3.726538e-03
## M11 1.670879e+00
## M2 2.190776e-01
## M3 2.429777e-01
## M4 1.265729e-01
## M5 7.403493e-02
## M6 1.017192e+00
## M7 3.347305e-01
## M8 1.846254e-01
## M9 1.663198e+01
## CNG 2.493646e-02
## Diesel 1.377247e+00
## Petrol 8.712612e-01
## 113Nm@4400rpm 1.014486e+00
## 170Nm@4000rpm 1.670879e+00
## 200Nm@1750rpm 1.663198e+01
## 200Nm@3000rpm 7.403493e-02
## 250Nm@2750rpm 1.265729e-01
## 60Nm@3500rpm 3.627505e-03
## 82.1Nm@3400rpm 1.846254e-01
## 85Nm@3000rpm 3.726538e-03
## 91Nm@4250rpm 2.429777e-01
## 113.45bhp@4000rpm 1.265729e-01
## 118.36bhp@5500rpm 1.670879e+00
## 40.36bhp@6000rpm 3.627505e-03
## 55.92bhp@5300rpm 1.846254e-01
## 61.68bhp@6000rpm 3.726538e-03
## 67.06bhp@5500rpm 2.429777e-01
## 88.50bhp@6000rpm 1.014486e+00
## 88.77bhp@4000rpm 7.403493e-02
## 97.89bhp@3600rpm 1.663198e+01
## 1.0 SCe 2.429777e-01
## 1.2 L K Series Engine 3.347305e-01
## 1.2 L K12N Dualjet 2.190776e-01
## 1.5 L U2 CRDi 1.265729e-01
## 1.5 Turbocharged Revotorq 7.403493e-02
## 1.5 Turbocharged Revotron 1.670879e+00
## F8D Petrol Engine 3.627505e-03
## G12B 3.726538e-03
## i-DTEC 1.663198e+01
## K Series Dual jet 1.017192e+00
## K10C 1.846254e-01
## Disc 1.265729e-01
## Drum 3.980571e-02
## transmission_type_Automatic 3.304209e-01
## transmission_type_Manual 1.766381e-01
## steering_type_Electric 6.703357e-02
## steering_type_Manual 3.726538e-03
## steering_type_Power 4.284768e-02
# Visualize feature contributions to the first principal component
fviz_contrib(mca_result, choice = "var", axes = 1, top = 10)
# Visualize feature contributions to the second principal component
fviz_contrib(mca_result, choice = "var", axes = 2, top = 10)
# Visualize variable coordinates with color representing cos2 values
fviz_mca_var(mca_result,
col.var = "cos2", # Color by cos2 values
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE) # Avoid label overlap
# List of categorical features
categorical_features <- c(
'region_code', 'segment', 'model', 'fuel_type', 'max_torque', 'max_power',
'engine_type', 'rear_brakes_type', 'transmission_type', 'steering_type'
)
# Extract categorical feature data
categorical_data <- car_data2 %>%
select(all_of(categorical_features))
# Perform MCA
mca_result <- MCA(categorical_data, graph = FALSE)
# Visualize only the most contributing variables (e.g., top 20)
fviz_mca_var(mca_result,
title = "MCA - Variables (Top 20)",
label = "var", # Label type: "var" or "ind"
select.var = list(contrib = 20), # Show only the top 20 contributing variables
repel = TRUE) # Avoid label overlap
# Specify the categories to display
specific_categories <- c("Diesel", "Petrol", "CNG", "Automatic", "Manual")
# Visualize only the specified categories
fviz_mca_var(mca_result,
title = "MCA - Specific Variables",
label = "var", # Label type: "var" or "ind"
select.var = list(name = specific_categories), # Display only specific categories
repel = TRUE) # Avoid label overlap
# Read data
car_data2 <- read.csv("~/Downloads/car_data2.csv")
# List of numerical features
numeric_features <- c(
'subscription_length', 'vehicle_age', 'customer_age', 'region_density',
'airbags', 'displacement', 'cylinder', 'turning_radius', 'length', 'width',
'gross_weight', 'ncap_rating'
)
# Extract numerical feature data
numeric_data <- car_data2 %>%
select(all_of(numeric_features))
# Standardize data
scaled_data <- scale(numeric_data)
# Randomly sample a portion of the data
set.seed(123)
sample_indices <- sample(1:nrow(scaled_data), size = 10000)
sample_data <- scaled_data[sample_indices, ]
# Determine the optimal number of clusters using the elbow method
fviz_nbclust(sample_data, kmeans, method = "wss")
# Determine the optimal number of clusters using the silhouette method
fviz_nbclust(sample_data, kmeans, method = "silhouette")
# Assume 4 clusters are chosen
set.seed(123)
kmeans_result <- kmeans(scaled_data, centers = 4, nstart = 25)
## Warning: Quick-TRANSfer stage steps exceeded maximum (= 2929600)
# View clustering results
print(kmeans_result)
## K-means clustering with 4 clusters of sizes 14018, 15068, 21872, 7634
##
## Cluster means:
## subscription_length vehicle_age customer_age region_density airbags
## 1 0.16812731 0.3473222 -0.005357985 -0.10329599 1.5621898
## 2 -0.41290194 -0.7959423 0.085899130 0.17599892 -0.6293245
## 3 0.14704896 0.2724309 0.017936543 -0.05108790 -0.3270899
## 4 0.08495453 0.1527231 -0.211098761 -0.01133795 -0.6892853
## displacement cylinder turning_radius length width gross_weight
## 1 1.2416005 0.7713501 1.52199364 1.4432905 1.0506490 1.5757383
## 2 -1.3511277 -1.2627851 -1.11592575 -1.2897293 -1.4083715 -0.9177984
## 3 0.3217680 0.7370325 -0.07423063 0.1571996 0.5616518 -0.2397034
## 4 -0.5349322 -1.0355665 -0.37948197 -0.5549745 -0.7585936 -0.3951426
## ncap_rating
## 1 0.89239408
## 2 -1.26625053
## 3 0.31189508
## 4 -0.03294294
##
## Clustering vector:
## [1] 1 3 1 2 3 3 1 3 4 3 3 2 1 2 2 3 2 3 3 4 3 3 1 1 2 2 3 4 2 3 3 2 3 4 2 3
## [37] 3 1 4 3 3 2 2 1 3 1 2 2 4 3 3 2 3 3 3 1 3 1 3 1 4 2 3 2 3 3 3 2 2 3 3 3
## [73] 2 4 1 3 3 3 2 1 1 4 1 1 2 1 2 2 2 3 3 2 2 3 4 1 4 3 2 1 1 2 4 2 1 3 1 3
## [109] 4 2 1 2 4 2 1 3 2 1 3 3 1 2 4 2 1 3 1 3 3 4 2 3 3 1 2 1 3 3 3 1 3 2 3 3
## [145] 4 3 1 4 2 1 2 2 2 4 2 3 1 2 3 3 2 3 1 2 3 1 2 1 1 4 2 4 2 3 3 3 1 2 3 3
## [181] 2 3 1 3 2 3 3 3 1 2 1 3 1 3 3 4 1 4 1 1 2 2 3 3 3 1 3 3 3 4 3 2 1 3 3 1
## [217] 3 4 2 3 1 4 1 3 2 3 3 4 1 3 4 1 2 3 3 2 3 2 2 1 1 1 1 2 3 3 4 3 3 2 1 3
## [253] 2 3 2 2 1 4 2 3 2 2 2 3 2 3 3 3 2 3 1 1 4 2 2 1 3 1 4 4 3 1 3 2 4 4 4 1
## [289] 4 3 3 3 3 1 3 3 4 2 4 4 2 3 2 1 1 3 1 4 2 3 4 2 3 2 2 4 3 3 3 1 2 3 1 4
## [325] 2 2 4 1 2 3 3 3 2 4 3 1 2 3 4 3 3 3 3 4 3 1 1 2 2 4 2 3 1 1 3 3 4 2 3 3
## [361] 3 4 3 1 2 3 2 3 3 2 2 1 2 2 2 2 1 1 3 3 1 3 4 1 1 2 3 3 3 3 3 3 2 2 1 1
## [397] 1 4 1 1 4 2 1 2 2 4 3 3 1 3 3 2 4 1 1 3 2 2 1 3 3 3 4 3 2 1 1 4 3 1 1 3
## [433] 3 1 3 3 2 3 2 3 3 2 1 2 1 3 3 3 3 3 1 4 3 2 4 4 1 1 1 3 1 4 3 3 3 4 2 3
## [469] 2 1 2 1 3 4 1 1 2 3 2 3 1 3 1 3 3 2 3 3 4 2 4 1 3 3 1 3 2 4 4 4 3 3 3 3
## [505] 1 4 4 2 3 3 3 3 1 4 2 1 3 4 1 1 3 3 3 2 3 2 4 3 3 2 3 3 1 3 3 3 3 2 4 2
## [541] 3 2 2 1 2 2 2 2 4 1 3 3 2 2 3 1 3 1 2 3 4 1 3 3 2 2 1 3 1 1 2 4 2 2 1 3
## [577] 4 4 2 4 4 3 1 1 1 1 3 3 1 3 1 3 4 2 2 1 1 3 3 3 2 4 4 1 2 3 1 1 3 2 3 3
## [613] 1 2 3 3 1 3 3 3 3 2 2 2 3 2 1 4 3 3 3 3 2 2 3 4 2 4 3 1 2 3 2 3 3 2 1 3
## [649] 3 2 2 3 3 3 2 4 2 1 3 3 2 3 3 3 1 1 4 3 2 4 1 3 3 4 2 2 3 1 2 4 1 3 4 3
## [685] 3 2 4 2 3 2 3 2 3 3 3 1 3 4 4 2 1 4 1 3 4 3 1 3 1 2 1 3 2 2 1 2 2 2 3 2
## [721] 3 2 3 4 2 1 3 2 3 1 4 3 1 4 3 1 3 4 1 4 2 3 4 1 3 1 3 2 1 3 4 3 4 3 2 1
## [757] 3 4 3 1 1 3 2 2 3 4 3 3 1 3 1 1 3 2 4 2 3 4 2 4 1 1 3 4 3 3 3 3 1 2 1 3
## [793] 2 4 4 3 3 2 2 1 2 3 3 3 2 3 4 2 4 3 3 1 3 1 2 3 4 1 3 1 3 2 1 3 2 2 1 1
## [829] 1 3 4 2 1 1 2 3 3 4 3 3 3 3 3 2 1 1 3 3 3 2 2 2 1 3 3 3 1 1 3 2 2 1 3 4
## [865] 4 1 2 1 4 2 1 1 3 1 4 1 3 1 3 1 3 3 2 1 3 4 1 2 3 1 3 4 2 4 4 2 3 1 1 3
## [901] 2 2 1 2 3 1 2 2 3 3 2 1 3 3 3 3 1 1 1 1 2 3 2 3 2 4 4 3 2 1 2 2 3 1 1 2
## [937] 1 4 3 3 2 1 1 3 2 3 4 3 2 1 4 1 4 1 4 3 3 3 2 3 3 3 2 4 3 4 2 2 2 2 3 4
## [973] 2 3 1 3 4 1 3 3 4 4 4 3 2 1 1 2 3 2 2 4 4 3 3 1 1 3 2 1 3 3 2 3 3 3 3 3
## [1009] 1 3 3 2 3 3 3 2 3 3 1 1 3 3 3 3 1 2 3 2 4 2 3 1 3 3 4 2 3 3 3 2 1 3 1 4
## [1045] 3 2 1 2 3 1 4 1 4 1 2 3 1 3 4 4 3 2 1 3 2 3 3 2 3 4 3 4 2 1 1 1 1 3 2 2
## [1081] 4 3 3 3 2 4 1 1 2 1 2 2 3 1 3 1 4 2 3 1 3 1 3 2 2 3 1 2 2 3 1 1 3 2 3 3
## [1117] 3 3 3 3 2 3 3 2 1 3 3 1 4 4 1 3 2 3 2 3 3 2 2 1 3 4 2 3 3 2 3 3 2 4 1 3
## [1153] 1 3 3 3 1 1 3 3 1 3 1 3 2 3 4 3 2 2 3 2 2 2 4 3 3 2 2 1 4 3 2 3 3 2 1 3
## [1189] 1 3 1 3 1 3 3 1 2 3 3 2 2 3 3 1 1 3 1 3 3 3 2 2 3 3 2 3 4 2 2 3 3 4 3 1
## [1225] 2 2 3 3 3 4 3 4 3 3 3 4 2 1 2 4 3 3 3 3 1 2 2 1 2 3 1 3 2 3 3 4 1 3 1 3
## [1261] 2 1 4 3 3 2 2 1 1 2 1 1 3 3 2 1 2 1 2 1 2 4 1 2 2 1 3 1 3 1 3 4 2 3 1 2
## [1297] 3 3 4 1 3 1 3 3 4 2 4 2 3 3 3 2 2 1 3 3 1 2 1 1 3 2 1 2 3 2 3 4 2 2 3 4
## [1333] 2 2 1 2 3 3 3 1 3 3 3 2 1 3 4 2 1 1 2 3 1 3 3 3 4 2 1 2 3 1 1 3 1 2 1 1
## [1369] 3 2 2 2 1 1 3 3 4 2 3 2 3 2 2 1 4 3 3 2 2 1 3 1 1 3 3 3 4 3 4 3 2 3 1 2
## [1405] 3 2 4 4 2 3 2 2 1 1 3 3 3 3 3 2 4 1 2 1 2 3 3 2 3 3 3 3 3 2 2 2 2 1 3 4
## [1441] 3 3 3 4 4 3 1 4 3 3 1 1 3 2 3 1 1 2 3 2 4 4 3 3 3 1 1 3 4 3 3 3 1 2 3 3
## [1477] 4 1 1 4 3 3 2 1 3 2 3 3 1 4 2 3 2 2 2 2 3 2 4 3 2 1 2 2 3 2 3 3 1 2 2 1
## [1513] 2 3 4 4 2 3 2 1 3 4 1 1 2 3 3 3 1 1 3 3 2 1 1 3 2 2 2 1 2 1 2 3 1 1 4 1
## [1549] 3 3 2 3 1 3 1 3 1 4 3 2 1 4 2 1 1 3 3 1 3 2 3 1 2 4 2 3 4 4 3 2 3 4 3 2
## [1585] 3 1 3 1 3 1 2 3 3 4 4 4 3 3 1 3 3 2 2 1 2 4 2 2 4 2 3 2 1 3 1 4 1 2 2 4
## [1621] 4 3 2 4 1 3 3 1 3 3 3 3 3 4 2 4 3 3 3 3 2 1 2 3 3 2 3 3 4 3 3 2 2 1 3 3
## [1657] 2 2 4 1 3 3 2 2 1 4 3 1 2 1 3 3 3 2 2 4 1 3 2 3 2 4 4 1 2 3 1 1 3 1 2 3
## [1693] 4 1 3 1 1 3 1 1 1 2 3 1 1 2 2 1 3 2 3 1 2 1 3 1 3 2 3 2 3 1 4 2 4 1 2 1
## [1729] 3 3 1 2 3 3 2 2 2 1 2 1 3 3 1 1 1 3 4 2 3 4 4 1 4 3 4 2 1 2 1 1 2 2 4 2
## [1765] 4 3 1 2 3 1 1 1 3 2 3 2 3 3 3 3 2 3 1 2 3 4 1 3 1 2 3 1 3 1 3 3 3 2 3 2
## [1801] 2 4 1 3 3 1 3 1 2 4 2 3 3 1 1 2 2 3 3 4 4 3 4 2 1 3 1 2 1 3 2 1 1 2 4 3
## [1837] 2 3 2 4 3 3 3 4 1 3 3 4 1 2 3 4 1 3 3 3 3 3 3 4 2 3 1 1 1 2 4 3 4 3 2 3
## [1873] 1 3 1 4 1 2 4 3 2 2 3 3 3 1 2 1 3 4 3 3 3 4 3 3 1 3 2 3 1 1 2 2 4 2 2 3
## [1909] 3 2 3 3 3 1 2 1 2 3 1 3 4 3 3 3 1 2 3 3 4 1 1 3 1 2 3 1 1 2 2 3 2 3 3 2
## [1945] 1 1 4 3 2 3 3 1 4 1 2 3 3 1 2 1 2 4 3 3 1 1 2 4 3 3 4 1 3 3 3 1 3 3 2 2
## [1981] 2 2 3 2 1 3 3 1 3 1 4 2 2 4 1 1 3 2 3 3 1 1 2 1 4 2 3 1 2 4 3 2 3 1 2 2
## [2017] 4 4 1 2 4 3 4 3 2 1 4 1 3 1 2 1 1 3 1 3 3 1 2 2 2 2 3 4 1 1 3 3 2 1 2 2
## [2053] 1 1 1 3 3 2 3 4 1 1 3 1 3 1 3 3 1 3 2 1 2 2 1 1 4 3 2 1 3 3 4 3 4 1 2 3
## [2089] 1 3 3 3 3 1 2 3 2 1 1 3 2 1 3 3 4 3 4 3 3 4 1 2 3 1 3 3 3 3 4 4 4 3 3 1
## [2125] 3 1 1 1 3 3 1 3 1 2 4 3 3 2 3 1 2 4 2 2 3 4 3 3 4 1 3 2 3 4 1 3 1 3 3 3
## [2161] 3 1 3 2 3 2 1 3 2 4 3 1 1 3 3 2 2 2 2 1 1 3 3 2 1 1 2 2 2 2 3 2 1 1 3 2
## [2197] 3 2 3 3 3 2 3 1 4 1 1 1 1 3 3 4 2 3 3 1 1 3 3 2 3 2 3 1 3 3 4 3 3 1 1 3
## [2233] 1 1 2 1 2 1 3 2 2 3 3 3 2 4 2 4 1 4 2 1 3 2 1 3 4 1 1 3 4 3 3 1 1 3 2 4
## [2269] 4 3 3 2 3 3 2 3 3 4 3 1 2 4 2 3 1 2 1 2 2 2 1 3 2 3 1 1 3 3 4 3 3 1 1 3
## [2305] 2 2 1 2 1 2 3 4 2 1 3 3 3 3 2 3 1 2 1 1 3 2 1 4 2 4 1 3 2 3 2 4 3 3 2 4
## [2341] 3 3 3 1 4 1 3 2 1 3 3 3 3 4 4 3 3 2 1 3 1 1 3 4 2 3 2 2 3 3 3 2 4 3 2 2
## [2377] 2 3 1 2 2 2 4 1 1 2 2 3 3 3 2 2 1 3 2 4 1 1 2 1 4 3 2 4 3 3 3 3 2 4 4 3
## [2413] 2 1 1 3 3 4 3 2 3 4 3 4 3 1 4 3 3 1 2 3 2 3 3 2 4 3 1 3 2 2 2 2 4 3 3 2
## [2449] 2 1 1 3 3 4 1 3 3 3 1 2 3 2 2 2 4 1 1 3 2 1 3 3 2 1 3 4 2 4 3 3 3 1 3 3
## [2485] 2 3 3 4 3 1 3 3 1 2 4 4 3 4 3 3 2 1 2 2 4 1 2 3 2 4 1 1 2 1 4 3 3 3 2 1
## [2521] 2 3 3 2 1 1 4 1 3 2 3 2 3 3 1 3 4 3 2 3 1 4 3 2 4 3 3 2 3 3 3 2 4 4 3 4
## [2557] 2 4 1 1 3 4 3 2 3 4 4 3 3 1 1 3 1 2 1 2 1 3 3 1 3 4 3 2 1 2 2 1 2 2 3 3
## [2593] 2 2 3 2 3 2 1 1 3 3 1 1 1 3 3 1 3 1 1 1 3 2 2 1 2 1 2 3 2 3 3 4 3 3 1 3
## [2629] 1 3 1 1 3 3 1 2 4 3 4 3 1 3 1 2 3 3 1 1 3 2 3 2 3 1 3 2 3 2 3 1 2 3 1 1
## [2665] 2 3 3 2 2 2 1 1 2 2 1 1 2 1 4 2 1 3 3 2 2 3 4 3 2 4 2 4 3 4 3 3 1 1 1 1
## [2701] 4 4 3 4 2 3 3 2 2 3 1 3 4 4 1 1 3 2 1 4 4 3 3 2 3 1 2 1 3 1 3 1 2 4 3 3
## [2737] 3 1 2 3 4 1 4 2 2 1 2 3 4 4 4 2 3 3 3 3 3 3 3 3 3 4 1 3 2 3 4 2 2 1 4 4
## [2773] 1 2 2 2 3 4 2 2 2 2 1 2 3 3 1 2 2 2 1 2 4 4 2 3 4 3 4 2 1 3 3 1 3 3 3 2
## [2809] 1 3 3 3 1 3 2 3 4 3 2 2 3 3 3 3 2 4 3 3 4 2 2 1 2 2 2 3 2 3 1 2 3 1 3 2
## [2845] 4 2 2 2 2 1 4 3 4 2 3 3 3 4 2 2 2 1 2 2 2 3 3 2 3 1 3 1 2 3 3 3 3 3 2 1
## [2881] 1 4 4 2 2 4 1 2 3 1 2 3 4 3 1 2 1 3 3 2 2 1 3 3 4 2 4 4 2 3 3 1 3 4 3 1
## [2917] 1 4 3 3 2 3 2 4 3 4 1 3 1 3 3 3 2 3 1 2 4 4 3 3 2 4 2 2 3 4 2 3 4 3 1 2
## [2953] 2 1 3 3 2 2 3 1 4 2 3 3 2 4 4 3 1 4 2 1 3 1 1 1 4 3 3 3 4 2 3 2 2 3 3 3
## [2989] 1 2 3 1 1 2 2 3 3 2 1 3 3 3 1 1 4 3 3 1 2 3 2 3 1 3 1 3 2 3 2 2 4 2 1 4
## [3025] 3 3 1 3 3 2 3 2 1 2 3 2 1 3 3 1 1 3 4 2 3 3 1 3 3 3 3 2 3 3 3 3 3 2 2 3
## [3061] 4 4 1 2 2 4 2 1 2 2 4 3 3 1 2 3 3 1 2 1 1 3 2 2 4 2 2 3 2 4 3 1 3 3 4 4
## [3097] 3 3 2 3 3 1 3 1 2 3 1 2 1 3 3 3 1 2 1 3 1 4 1 1 2 3 4 1 1 3 2 4 4 2 3 1
## [3133] 3 2 2 2 4 3 4 3 2 1 3 1 3 4 4 1 3 3 3 1 3 2 3 2 3 2 1 3 2 3 3 3 2 3 4 1
## [3169] 2 3 3 2 1 4 3 2 1 1 4 3 2 3 2 1 2 2 3 1 3 1 2 2 4 3 1 3 1 1 2 2 3 3 1 2
## [3205] 2 1 1 1 3 3 1 2 1 4 3 4 1 2 2 3 4 2 4 3 3 4 4 3 1 4 2 3 1 3 4 3 3 2 1 4
## [3241] 3 4 1 3 1 3 1 2 1 2 3 2 1 4 3 4 1 4 2 1 4 1 3 2 2 3 1 1 3 3 4 2 4 3 2 3
## [3277] 2 1 3 2 4 3 4 2 2 3 1 3 4 4 3 1 3 4 4 3 1 3 1 4 4 2 3 3 1 1 4 4 1 2 1 1
## [3313] 1 1 3 3 2 3 2 3 2 1 2 4 2 3 2 1 3 3 2 3 2 1 2 3 3 4 3 3 3 2 4 4 4 2 4 1
## [3349] 2 2 3 1 1 2 3 2 1 2 2 2 2 2 3 1 1 3 2 1 3 3 4 2 4 1 3 3 3 1 2 2 2 2 4 2
## [3385] 1 3 1 4 3 3 4 2 2 1 3 1 1 1 3 1 2 2 2 3 1 3 3 2 1 3 1 3 2 2 4 2 1 4 3 4
## [3421] 3 2 3 2 2 1 2 3 1 3 2 1 4 2 2 2 1 3 4 2 1 2 3 3 2 3 1 2 1 3 2 3 3 4 3 3
## [3457] 2 2 2 1 2 2 1 1 1 1 4 2 3 2 3 2 4 4 2 3 2 4 4 1 3 1 3 3 2 2 1 1 3 1 2 4
## [3493] 3 2 2 4 3 3 2 3 1 1 2 3 3 1 2 1 2 3 3 3 3 2 1 1 2 3 4 2 2 3 4 3 3 2 2 3
## [3529] 4 1 1 4 1 3 1 2 4 3 2 1 2 2 1 2 1 3 1 2 2 3 3 2 2 1 2 3 3 4 1 4 4 3 4 2
## [3565] 4 2 2 3 2 3 3 1 3 2 2 2 3 1 3 3 2 3 1 2 3 3 4 3 3 3 2 2 3 3 3 2 1 1 3 4
## [3601] 1 3 2 4 2 3 1 3 4 3 4 1 3 2 1 2 3 2 2 4 3 3 3 1 3 3 1 4 2 2 3 2 1 1 1 2
## [3637] 3 1 4 4 3 1 3 4 1 4 3 1 3 1 3 3 1 3 2 4 4 1 3 3 3 3 4 3 3 3 3 3 2 1 1 3
## [3673] 2 4 1 1 4 4 4 2 3 1 2 3 3 1 2 3 2 3 1 2 4 4 3 3 4 3 1 2 3 2 2 1 1 3 1 2
## [3709] 4 1 4 2 3 2 4 3 2 2 2 1 3 2 1 1 3 1 1 2 3 2 1 2 3 2 4 3 2 4 1 2 3 2 2 2
## [3745] 2 4 3 3 2 3 1 2 1 2 2 1 1 3 1 3 2 3 1 1 4 1 3 1 3 2 3 1 1 2 3 2 1 4 3 3
## [3781] 3 1 2 3 3 4 3 3 3 3 1 3 3 1 1 1 2 2 1 1 2 4 4 3 3 3 2 3 2 1 3 2 1 1 3 1
## [3817] 3 1 1 3 2 3 1 2 2 1 3 1 3 1 2 2 2 3 2 4 2 2 1 3 3 1 3 3 2 2 2 1 1 2 2 2
## [3853] 3 2 1 1 2 3 4 3 2 3 2 3 3 2 1 2 4 3 4 2 2 4 3 1 2 3 1 3 1 3 2 3 2 2 1 3
## [3889] 4 1 4 3 3 4 3 2 4 1 4 1 2 2 2 2 3 3 1 2 2 2 3 4 3 1 3 2 1 4 2 1 2 3 1 2
## [3925] 2 2 4 1 1 2 3 2 2 3 1 3 3 3 3 3 2 3 3 3 2 3 2 1 2 3 3 1 3 4 1 1 2 1 2 2
## [3961] 1 2 3 3 1 3 3 3 3 3 2 3 3 3 1 2 2 3 1 3 3 3 4 1 2 2 1 1 4 2 4 3 3 2 2 3
## [3997] 1 2 3 3 1 3 3 4 3 1 3 2 2 3 2 2 1 2 2 1 1 3 1 3 2 1 3 3 1 3 1 2 2 1 2 2
## [4033] 4 2 3 1 4 3 1 3 3 3 2 3 1 3 3 3 1 4 1 1 3 2 3 4 4 2 2 2 2 1 3 2 4 1 4 2
## [4069] 4 2 1 4 3 2 4 4 3 1 1 2 2 1 3 4 2 3 3 1 3 2 1 3 3 3 4 4 2 3 2 1 2 1 3 1
## [4105] 1 2 2 1 1 3 2 3 1 1 3 4 3 2 3 4 3 4 4 2 3 2 3 3 3 1 2 1 3 1 3 2 1 3 3 4
## [4141] 2 1 2 4 2 3 2 4 2 3 3 3 2 4 1 3 1 3 3 2 2 1 4 1 1 3 3 4 1 2 4 4 2 1 3 2
## [4177] 4 1 2 3 3 3 3 2 3 1 4 4 3 4 1 2 3 1 3 1 3 2 3 3 3 4 2 3 2 1 3 3 3 2 1 3
## [4213] 3 1 3 3 3 3 1 4 1 2 3 2 3 1 2 4 3 3 1 2 3 2 2 3 2 4 3 4 3 2 2 1 2 3 3 4
## [4249] 1 1 4 2 3 2 3 4 1 2 4 1 3 3 3 1 4 3 1 1 3 4 3 3 1 3 3 4 2 4 3 2 4 1 4 1
## [4285] 3 2 3 1 2 4 3 3 2 3 4 3 4 3 3 3 3 2 1 3 2 3 3 3 3 4 2 2 2 1 3 1 4 2 3 3
## [4321] 3 3 3 1 1 4 3 2 3 3 3 3 3 4 2 4 4 2 1 3 3 1 4 4 3 3 4 3 1 4 4 4 3 3 4 4
## [4357] 2 2 1 4 3 1 4 1 2 3 3 4 2 1 1 4 3 3 1 1 3 3 2 3 3 4 4 3 3 4 3 1 3 3 4 1
## [4393] 3 1 1 1 1 1 1 4 1 3 3 1 1 2 2 3 3 3 2 2 2 2 3 3 1 2 1 1 1 2 2 3 4 1 3 1
## [4429] 1 3 2 1 3 1 2 3 1 4 2 1 2 4 2 2 4 3 1 4 4 2 3 2 2 1 3 1 3 3 1 3 3 4 3 1
## [4465] 3 1 2 3 3 2 2 3 2 3 3 3 2 3 1 4 2 4 2 2 3 2 3 3 1 2 1 3 4 3 2 2 3 3 4 3
## [4501] 4 1 3 3 3 3 3 3 4 3 3 4 2 4 3 4 3 3 3 4 3 2 1 2 3 3 2 4 1 2 3 4 4 3 4 3
## [4537] 1 1 2 3 3 2 1 2 3 2 1 4 3 4 4 2 2 3 4 1 2 4 1 1 4 1 3 2 4 1 3 2 3 3 4 2
## [4573] 3 3 3 1 4 3 3 3 3 4 3 2 4 3 3 1 2 1 2 1 1 2 2 4 3 3 2 1 4 2 2 3 3 3 2 3
## [4609] 2 1 2 3 2 3 4 3 1 3 3 3 1 3 2 1 4 3 1 2 2 3 3 2 3 1 3 1 2 2 3 1 3 2 1 2
## [4645] 2 3 1 3 3 3 2 3 3 2 1 1 2 2 1 3 2 1 2 1 3 3 2 3 2 3 1 2 4 4 3 3 3 3 4 1
## [4681] 2 3 1 2 2 2 4 1 1 4 3 2 3 4 4 1 3 3 2 4 2 1 3 2 3 4 3 1 1 2 3 3 1 3 1 1
## [4717] 2 3 3 3 1 2 1 3 4 1 3 3 3 1 4 1 1 3 1 3 3 2 1 2 4 1 1 2 3 2 3 3 4 3 3 4
## [4753] 2 3 4 1 3 2 4 1 3 3 3 2 3 1 2 3 1 4 3 3 1 3 2 3 1 3 1 3 3 2 2 1 3 3 4 4
## [4789] 3 3 4 3 3 2 3 3 3 4 3 2 1 2 1 4 2 1 2 2 1 1 1 2 2 3 4 3 2 1 3 3 3 3 2 2
## [4825] 3 2 4 1 4 2 2 3 1 3 4 1 2 2 4 1 3 4 3 3 1 3 3 3 4 1 2 1 2 2 3 1 1 3 4 3
## [4861] 2 3 3 2 3 3 1 4 1 1 3 3 3 4 3 1 1 4 1 1 3 1 1 1 2 3 3 4 3 3 2 4 4 3 1 2
## [4897] 3 2 2 1 2 1 4 4 3 3 2 4 2 4 2 3 2 3 2 1 2 1 3 2 3 2 1 3 2 1 4 3 2 3 3 1
## [4933] 3 3 4 3 1 3 4 1 1 2 3 3 2 1 1 1 1 3 3 2 2 2 1 3 2 2 2 3 2 1 3 2 2 3 4 3
## [4969] 1 1 3 1 4 3 2 4 1 1 1 2 4 1 1 3 2 1 3 2 4 3 1 1 1 2 4 2 4 1 1 4 3 1 3 1
## [5005] 3 4 3 1 1 3 1 3 2 1 1 4 4 3 3 2 3 4 3 1 3 3 3 3 1 3 4 3 4 2 3 4 1 3 1 1
## [5041] 4 3 3 2 1 1 4 3 3 1 1 1 2 2 3 1 2 3 1 4 3 4 3 4 2 3 1 3 1 1 2 1 3 1 2 3
## [5077] 2 4 1 1 4 2 3 3 1 3 1 3 1 1 2 4 1 4 1 3 4 2 3 2 3 3 3 3 1 4 3 2 3 3 3 2
## [5113] 3 1 1 2 4 2 2 1 4 1 3 1 1 4 2 2 2 2 4 1 4 1 3 2 1 2 2 1 3 2 2 1 2 2 3 4
## [5149] 1 1 3 2 2 4 1 1 4 2 2 3 2 3 2 3 2 1 2 1 2 2 3 3 4 4 2 1 2 3 3 1 2 3 4 1
## [5185] 1 4 2 1 2 3 3 3 1 3 4 3 1 2 1 2 2 1 3 1 4 1 2 2 4 1 4 4 3 1 3 1 3 1 3 3
## [5221] 2 3 4 3 1 1 3 4 4 1 3 3 1 1 2 2 2 4 1 2 3 2 3 4 2 2 1 3 2 2 3 3 3 1 1 3
## [5257] 3 2 1 2 2 1 4 3 4 2 2 3 3 3 4 1 1 1 2 3 2 3 2 1 2 3 3 3 3 2 1 3 3 3 1 3
## [5293] 2 2 3 2 3 2 4 1 1 1 2 3 2 2 3 3 2 1 3 2 2 1 1 2 1 1 1 2 3 3 1 1 1 3 2 3
## [5329] 3 1 4 2 3 2 3 3 3 2 3 1 1 4 4 1 2 4 1 1 3 3 1 4 3 3 3 2 2 2 1 2 3 1 3 4
## [5365] 1 2 3 1 4 3 1 1 4 3 3 4 1 2 2 1 3 1 2 3 2 2 3 2 3 3 3 4 4 1 3 2 3 1 2 3
## [5401] 2 4 3 3 3 3 2 1 2 2 1 1 2 1 2 2 1 2 1 3 2 3 3 1 2 1 3 4 3 2 1 2 3 4 3 2
## [5437] 3 1 3 3 1 3 4 2 3 2 3 4 3 2 2 1 3 4 2 3 3 2 1 2 2 1 4 3 4 1 2 3 2 2 2 1
## [5473] 3 4 2 3 3 3 3 4 3 2 2 3 3 1 2 1 3 1 1 1 1 3 3 1 2 2 1 3 3 1 3 2 2 4 3 2
## [5509] 3 1 1 1 2 1 3 4 3 1 3 4 4 1 2 2 3 1 1 3 3 2 3 4 1 1 1 3 3 4 2 2 2 4 3 3
## [5545] 2 3 2 1 4 2 2 1 1 2 4 3 2 3 2 3 2 4 3 3 4 2 4 2 1 1 1 2 4 3 2 1 3 3 4 3
## [5581] 3 2 3 2 4 1 1 1 2 3 3 4 1 3 2 2 3 3 3 3 3 1 2 4 3 1 2 1 2 3 3 3 1 3 1 1
## [5617] 3 1 3 3 1 2 3 1 4 2 3 1 4 3 3 4 2 1 2 4 2 1 3 3 1 2 3 2 3 3 3 3 1 3 2 3
## [5653] 4 3 3 3 3 1 3 2 1 3 3 2 3 3 3 3 2 3 1 2 3 2 2 3 3 1 1 4 4 3 1 1 3 3 2 1
## [5689] 1 3 1 4 1 3 1 1 3 3 4 3 4 3 3 3 4 3 3 3 2 2 2 3 1 3 3 4 2 3 1 4 4 3 4 2
## [5725] 3 2 3 3 4 4 2 3 4 3 2 1 3 1 2 2 1 3 3 1 2 2 1 3 3 1 3 3 4 3 1 4 3 1 4 2
## [5761] 2 2 1 3 2 3 3 3 3 3 2 3 3 3 2 1 2 3 1 2 1 2 2 2 3 2 4 1 1 3 3 3 3 3 2 3
## [5797] 2 4 1 2 3 3 3 2 2 2 2 3 3 4 1 3 2 2 2 4 3 3 3 3 4 2 1 3 3 3 4 2 3 2 3 2
## [5833] 1 3 4 2 3 4 3 4 2 2 3 3 2 1 3 4 1 4 3 3 4 4 1 3 4 3 1 1 2 4 2 2 4 1 2 4
## [5869] 1 2 1 3 3 1 3 2 1 2 4 2 1 4 3 1 3 4 3 3 3 3 4 2 1 4 4 3 2 3 2 1 1 2 3 4
## [5905] 3 1 1 2 3 1 1 1 2 3 1 3 1 3 1 4 3 2 4 3 1 2 3 1 3 2 4 1 1 3 1 2 2 1 2 2
## [5941] 3 1 3 4 3 2 3 2 2 2 2 3 2 3 1 1 2 3 4 2 3 2 4 3 2 4 4 1 2 1 2 2 3 2 3 1
## [5977] 1 3 4 1 4 3 1 1 2 4 3 4 3 3 1 4 3 4 3 2 4 3 3 1 4 3 3 2 3 3 1 1 2 2 3 3
## [6013] 3 2 3 3 1 3 1 2 2 1 1 1 3 3 1 4 1 1 2 3 3 1 1 2 3 3 3 2 3 1 2 2 1 3 2 3
## [6049] 4 3 2 1 3 1 1 3 2 3 1 2 1 3 3 1 3 1 4 2 2 1 3 3 2 2 2 3 4 4 3 2 3 2 2 2
## [6085] 1 3 1 3 2 2 2 1 2 4 2 4 2 1 2 1 3 2 3 4 2 3 2 3 1 3 2 2 3 2 3 4 2 3 3 3
## [6121] 3 1 1 2 3 2 3 1 3 1 4 3 3 1 3 2 3 2 3 3 2 2 3 3 3 1 1 3 4 2 4 3 3 3 3 4
## [6157] 2 1 2 2 2 2 1 3 2 4 2 4 4 1 2 3 3 2 1 2 4 2 1 3 4 3 2 2 2 2 1 3 1 1 1 2
## [6193] 1 3 2 3 4 3 2 3 3 1 3 3 2 1 3 3 3 2 1 3 4 3 2 3 3 3 2 2 1 2 1 2 3 2 3 4
## [6229] 4 3 1 1 2 3 2 1 4 2 1 1 4 1 2 4 1 2 3 1 4 3 3 1 3 2 1 4 3 2 1 2 2 3 2 2
## [6265] 2 2 4 4 3 3 2 1 3 4 2 2 4 2 2 1 4 3 2 1 3 2 3 3 3 1 2 3 3 2 2 1 4 2 2 1
## [6301] 3 3 1 2 2 4 1 1 2 2 1 1 1 3 1 2 1 3 1 2 3 2 2 4 2 3 2 4 2 1 2 1 1 2 1 3
## [6337] 3 2 3 2 3 1 3 4 3 4 4 3 1 2 2 4 1 1 2 3 3 3 3 3 1 3 4 2 3 2 3 3 1 2 2 3
## [6373] 3 1 3 4 1 3 3 2 3 2 3 2 1 1 1 2 3 1 3 3 3 1 4 3 1 1 2 2 3 3 3 4 3 2 3 2
## [6409] 1 3 4 2 4 3 2 3 4 1 2 2 3 1 4 2 3 1 3 3 1 3 2 1 3 1 3 2 2 2 4 2 3 3 2 4
## [6445] 3 1 1 2 1 2 2 3 1 1 3 4 1 3 1 4 2 3 1 2 3 2 2 4 2 2 3 3 3 3 3 3 1 3 1 2
## [6481] 1 2 4 1 3 1 3 1 1 3 3 1 1 1 3 1 1 1 4 4 4 4 2 3 2 2 3 4 2 3 1 3 4 3 4 3
## [6517] 3 3 3 1 3 3 3 3 2 4 3 1 3 3 2 4 3 2 4 2 1 4 3 1 3 2 3 1 3 3 3 1 3 3 1 2
## [6553] 2 3 2 1 1 1 2 3 2 3 2 3 2 3 3 2 3 2 1 1 3 3 1 1 2 2 2 1 3 1 3 4 2 3 1 3
## [6589] 2 2 3 1 3 3 2 2 2 2 3 3 2 2 3 3 1 3 4 2 1 3 3 2 3 3 3 4 3 3 2 1 3 2 1 3
## [6625] 3 3 2 2 1 3 2 1 2 3 2 2 2 3 1 2 1 3 1 2 3 1 4 2 3 4 4 2 2 3 1 2 2 1 2 3
## [6661] 1 3 2 1 4 2 3 3 4 1 2 2 2 3 1 2 4 2 3 1 2 4 4 4 4 2 3 3 3 2 3 4 2 3 3 3
## [6697] 2 2 2 3 1 2 4 3 3 3 3 4 2 3 3 1 3 3 3 1 3 2 4 2 1 2 1 1 4 3 2 2 3 3 2 2
## [6733] 3 3 3 1 2 4 3 1 3 3 4 1 2 3 3 4 3 1 3 3 3 4 2 2 2 3 1 2 3 3 3 3 2 1 2 2
## [6769] 3 3 3 2 4 3 4 2 4 1 1 1 2 3 1 3 3 1 1 2 3 2 1 2 4 1 3 2 1 3 2 1 3 2 4 4
## [6805] 3 1 1 1 3 2 3 2 3 3 3 1 1 2 1 2 2 2 2 3 1 2 3 2 4 3 1 1 1 1 4 3 3 4 3 3
## [6841] 1 1 2 4 3 1 2 2 1 3 2 3 1 1 3 4 2 4 1 1 3 1 3 2 1 2 1 2 4 1 3 4 1 4 3 3
## [6877] 3 3 4 1 4 1 3 1 3 1 4 4 2 2 3 3 4 1 2 1 4 3 2 4 2 4 3 3 3 4 4 4 3 2 1 3
## [6913] 1 4 3 2 3 3 3 4 4 2 2 3 1 2 3 3 1 2 1 3 2 2 4 1 3 3 3 1 1 3 2 1 4 1 4 2
## [6949] 2 2 2 2 3 1 4 3 1 3 3 1 2 1 4 3 1 2 3 3 3 4 3 1 1 4 1 1 3 4 2 1 1 1 1 3
## [6985] 2 3 3 4 4 2 3 3 3 1 3 1 3 4 3 2 3 1 3 3 1 3 4 1 3 3 4 3 1 2 1 2 3 2 3 3
## [7021] 3 3 3 3 3 1 4 3 4 3 3 1 3 4 2 3 1 3 1 1 2 2 4 3 1 3 2 2 2 3 1 3 2 1 2 4
## [7057] 4 1 1 3 3 2 3 3 2 3 2 2 3 2 2 2 4 1 2 3 3 2 4 3 4 1 1 3 2 3 3 1 3 2 3 3
## [7093] 2 4 4 3 1 1 3 1 3 3 2 1 3 2 3 2 2 2 3 1 1 3 1 3 3 4 4 3 3 2 2 4 3 3 2 3
## [7129] 2 3 1 3 2 1 3 1 3 3 1 1 1 3 2 2 2 4 2 4 2 4 3 2 1 4 1 3 3 3 1 2 2 4 2 3
## [7165] 3 2 3 1 4 1 3 3 1 1 3 3 3 1 4 2 3 2 3 2 1 2 2 2 3 1 1 3 3 2 2 2 3 4 3 2
## [7201] 3 2 4 1 3 4 3 1 1 3 1 4 2 1 1 3 3 4 4 3 3 2 2 4 4 3 2 1 3 1 4 3 1 1 3 2
## [7237] 4 3 2 3 4 4 1 3 1 4 3 3 3 2 1 1 4 3 2 3 1 3 2 4 3 2 1 2 3 2 1 3 3 3 1 1
## [7273] 2 1 1 3 4 1 1 3 3 2 1 3 1 2 1 2 3 4 3 3 3 1 2 3 1 4 1 1 3 2 2 3 2 3 1 2
## [7309] 2 2 3 2 4 3 1 2 1 2 2 3 1 1 2 3 3 2 3 2 3 2 2 2 3 3 3 3 2 2 3 2 4 3 3 3
## [7345] 3 1 1 3 3 3 3 3 2 3 3 3 1 1 4 2 3 2 2 3 1 3 2 2 2 1 2 3 3 1 1 3 3 4 2 4
## [7381] 3 2 1 3 3 3 4 1 1 3 1 1 3 1 1 1 3 3 3 2 1 2 3 2 1 3 1 3 2 3 1 2 3 1 3 3
## [7417] 3 4 3 1 2 2 2 1 2 1 3 4 4 3 1 3 2 3 3 3 3 1 4 4 1 3 1 2 1 4 2 2 2 4 2 3
## [7453] 4 3 1 2 2 3 3 2 4 1 3 2 4 3 3 3 2 2 3 4 2 2 3 1 2 1 3 4 3 3 1 3 1 1 1 1
## [7489] 1 3 3 2 2 2 3 2 2 3 3 4 1 1 1 1 3 4 4 1 3 1 2 3 1 1 1 4 3 1 3 3 2 1 2 1
## [7525] 3 3 2 2 1 1 1 2 4 2 2 2 3 1 4 2 1 3 1 1 2 2 1 3 1 3 4 2 1 4 2 2 3 2 1 3
## [7561] 2 2 3 3 2 2 2 3 3 4 1 1 3 2 3 2 1 1 2 2 2 2 3 2 3 2 2 3 1 3 3 4 4 1 2 1
## [7597] 3 2 2 3 3 4 3 1 1 1 2 3 1 3 3 1 3 1 2 3 4 1 2 1 3 4 1 4 3 2 3 4 3 2 2 2
## [7633] 2 3 4 3 3 3 3 1 1 3 2 3 1 4 2 1 1 3 4 2 3 3 4 1 2 4 3 1 2 2 1 4 2 3 1 3
## [7669] 1 1 3 2 3 3 3 3 3 4 1 2 1 3 1 2 2 1 3 2 4 4 1 3 3 3 4 3 1 3 1 2 1 4 3 1
## [7705] 2 2 2 2 3 3 2 2 1 3 1 3 3 3 1 3 2 1 1 2 1 2 1 1 1 4 3 1 3 4 2 4 2 2 4 3
## [7741] 3 1 4 2 3 1 2 1 2 3 2 3 3 1 3 3 3 1 1 4 1 1 3 2 4 3 2 1 3 3 4 2 3 1 1 2
## [7777] 3 1 1 3 3 1 4 4 4 4 3 2 4 2 3 1 4 4 1 3 2 1 3 4 1 3 4 1 4 3 3 3 3 4 3 3
## [7813] 3 4 1 1 2 2 4 2 2 1 3 2 3 1 3 2 3 2 1 4 4 3 1 3 4 3 2 2 3 1 2 3 1 1 2 3
## [7849] 2 3 1 4 3 3 3 3 4 2 1 4 3 1 3 1 3 1 2 2 2 3 1 1 3 1 2 3 1 3 3 3 1 3 1 3
## [7885] 3 3 3 3 4 4 3 3 4 2 3 1 1 3 1 4 2 1 4 3 2 2 4 3 4 3 4 2 1 1 3 3 2 1 2 1
## [7921] 3 4 1 2 2 3 3 2 2 4 1 1 3 4 4 2 1 4 3 4 1 3 3 2 2 1 1 2 4 2 4 3 2 1 4 4
## [7957] 1 4 4 3 2 3 3 4 2 2 4 1 3 2 3 2 1 2 1 1 1 2 2 2 4 3 3 1 4 2 2 4 2 3 3 2
## [7993] 2 3 4 1 3 3 1 2 3 3 4 2 4 2 3 2 3 1 3 1 4 4 1 3 3 3 2 4 2 4 3 2 3 3 2 2
## [8029] 4 1 4 1 3 3 1 1 1 3 2 1 2 4 1 3 1 4 2 1 3 3 2 4 3 1 1 3 2 3 1 3 2 4 2 3
## [8065] 3 3 3 3 2 2 2 1 4 3 2 2 3 1 1 3 3 2 3 4 3 4 3 3 4 3 2 2 1 3 3 2 2 2 2 2
## [8101] 3 2 1 3 2 3 3 2 2 3 3 4 3 1 3 1 2 4 1 1 3 1 1 1 2 2 3 3 3 3 3 3 3 3 3 2
## [8137] 3 1 3 1 4 3 1 1 1 4 2 3 4 3 2 2 1 1 1 3 1 3 3 2 2 1 2 2 3 3 3 1 3 1 3 3
## [8173] 3 4 2 3 2 4 4 3 4 1 3 3 3 4 3 2 3 2 2 3 3 1 1 3 3 3 3 2 1 3 1 1 3 3 3 4
## [8209] 3 3 4 4 1 3 2 2 3 1 1 2 3 4 3 3 3 1 2 3 3 1 2 3 2 2 1 3 1 4 1 2 2 1 1 1
## [8245] 3 2 3 2 3 1 1 3 3 4 2 4 1 3 4 1 3 3 1 3 1 4 4 3 2 2 1 3 3 1 3 1 1 3 3 3
## [8281] 2 3 2 3 3 3 3 3 2 2 2 3 1 3 3 2 3 2 4 3 3 2 1 1 3 3 1 3 2 2 1 1 4 1 4 2
## [8317] 3 4 3 3 4 2 3 3 1 2 1 3 2 1 1 3 2 3 3 3 4 2 1 2 4 1 3 4 4 1 4 3 2 4 2 3
## [8353] 1 3 2 3 3 3 3 1 3 3 1 1 4 1 4 1 3 3 3 3 3 2 2 2 4 2 2 2 3 1 3 3 1 2 4 3
## [8389] 3 4 4 4 3 3 1 2 3 4 2 1 4 3 3 3 3 3 3 1 2 2 2 2 2 1 3 3 1 3 3 4 1 1 3 2
## [8425] 2 1 1 2 4 1 1 3 1 3 2 2 3 2 1 4 2 1 3 3 4 4 1 3 2 3 3 4 3 3 4 1 1 4 1 2
## [8461] 1 3 3 3 2 1 2 2 2 1 3 1 4 3 3 2 4 3 2 3 3 2 3 3 2 1 3 1 3 4 1 3 2 3 3 4
## [8497] 4 2 3 4 1 2 2 3 1 1 3 3 3 1 1 3 2 1 3 4 3 3 1 3 2 3 3 4 2 3 2 2 3 1 3 3
## [8533] 3 1 3 2 2 3 3 1 4 3 3 4 3 1 1 3 3 4 3 3 3 2 4 2 2 3 3 1 2 3 1 3 3 4 1 3
## [8569] 4 1 1 3 2 2 2 3 3 2 3 3 4 4 2 2 3 3 2 2 3 1 2 1 2 1 3 1 3 4 3 1 1 2 3 3
## [8605] 2 3 1 3 3 3 1 2 3 3 3 3 2 3 2 3 1 3 1 1 2 3 4 2 3 1 3 3 1 1 3 3 3 1 1 4
## [8641] 1 3 3 2 2 3 1 3 2 3 2 3 3 3 3 3 1 2 2 1 3 3 2 1 3 4 4 3 3 3 1 1 1 1 3 1
## [8677] 3 3 2 4 4 3 2 3 2 1 4 3 3 2 3 1 4 2 2 4 2 4 2 2 1 1 2 1 2 2 3 1 3 3 2 2
## [8713] 4 1 2 4 3 4 2 2 3 3 2 1 2 3 3 3 3 3 3 4 2 3 1 4 3 3 1 3 1 2 3 2 2 1 3 4
## [8749] 1 1 1 3 1 1 1 3 4 3 3 3 2 1 3 2 4 3 4 4 3 3 2 3 4 1 3 3 2 2 2 1 3 2 1 4
## [8785] 4 2 1 2 3 3 4 3 1 3 1 4 3 3 4 2 1 2 3 1 1 3 3 2 4 2 3 1 3 3 2 2 3 3 2 3
## [8821] 3 3 2 2 2 3 1 3 4 2 1 4 2 3 4 2 1 3 3 1 3 3 1 4 4 3 3 1 3 1 1 3 2 2 2 1
## [8857] 3 1 4 3 1 1 2 3 4 1 1 1 4 1 2 1 2 3 2 3 3 3 3 1 1 3 2 2 1 1 3 2 2 3 4 2
## [8893] 2 2 2 2 1 2 2 2 2 1 3 2 4 1 3 3 1 3 3 3 2 2 1 2 3 3 2 1 1 3 1 2 3 1 3 3
## [8929] 4 1 1 3 2 3 2 1 1 2 3 4 3 3 1 4 3 2 2 4 3 2 3 3 3 4 3 1 1 3 3 3 1 4 2 4
## [8965] 1 1 1 3 3 3 1 2 3 2 3 1 3 2 3 2 3 3 1 3 2 3 3 3 3 3 3 3 3 1 3 2 2 3 3 3
## [9001] 2 3 3 1 1 1 4 2 3 3 2 3 4 3 3 3 3 4 3 3 2 2 2 2 1 3 3 1 1 1 3 2 3 3 3 3
## [9037] 3 3 4 3 4 3 1 1 2 2 1 1 1 3 1 1 3 2 2 1 2 4 1 1 2 2 1 2 2 4 3 1 3 1 2 1
## [9073] 1 2 3 2 2 2 1 2 3 1 1 1 2 1 2 2 4 3 1 2 3 1 2 4 3 3 1 2 2 2 3 3 4 1 3 1
## [9109] 2 2 2 2 3 1 4 3 3 3 3 1 3 4 2 4 2 4 2 1 2 4 1 3 3 2 1 3 1 1 2 1 1 2 2 2
## [9145] 1 2 3 2 1 2 3 3 2 1 3 1 2 1 2 3 3 1 1 1 1 3 2 2 2 2 3 3 1 2 3 3 2 2 4 4
## [9181] 2 3 4 4 4 3 3 3 3 3 1 2 3 2 1 3 4 3 4 2 3 3 3 2 1 3 4 2 4 3 2 2 3 3 3 1
## [9217] 3 1 4 4 2 4 1 3 1 2 2 3 2 4 3 1 1 2 3 2 3 2 3 1 3 3 2 4 2 3 2 3 2 1 3 2
## [9253] 1 2 2 3 3 3 3 2 3 3 3 1 1 2 1 3 3 1 1 1 2 3 2 2 3 1 2 1 3 1 2 3 3 3 1 3
## [9289] 3 3 1 1 2 3 4 4 3 3 2 4 3 4 3 3 4 3 2 4 1 1 4 3 2 3 3 1 3 2 1 1 2 2 3 3
## [9325] 2 2 3 3 3 3 3 2 3 3 3 2 4 3 3 3 2 1 3 1 1 4 2 1 3 4 1 4 3 3 3 1 1 2 1 3
## [9361] 3 2 3 1 1 3 1 4 1 2 2 2 3 2 3 3 4 2 2 1 3 1 1 2 3 3 3 2 1 3 3 4 2 1 2 1
## [9397] 2 2 3 1 3 2 4 1 3 1 3 3 4 3 3 1 2 2 2 3 2 1 3 2 1 1 3 2 1 1 3 4 3 3 3 3
## [9433] 1 3 2 1 1 2 2 4 2 4 3 1 3 1 4 4 2 4 3 1 2 3 4 1 3 1 3 4 3 3 2 3 3 3 3 2
## [9469] 3 2 2 3 3 4 2 3 2 3 3 1 1 3 3 1 1 2 2 2 2 4 2 2 2 3 3 4 3 2 2 3 2 3 3 3
## [9505] 1 2 1 3 1 1 4 3 1 3 4 1 4 4 2 1 2 1 2 3 3 4 3 4 4 1 4 1 3 3 2 3 4 1 2 4
## [9541] 3 4 1 2 2 3 2 4 3 1 1 3 2 3 3 3 1 4 3 1 1 3 3 4 3 3 2 2 4 3 1 1 1 2 1 1
## [9577] 2 1 3 2 3 1 3 1 1 2 2 1 4 2 1 4 3 3 1 1 1 1 1 4 3 3 3 2 3 4 2 1 3 3 4 2
## [9613] 3 3 3 1 2 3 2 3 3 2 2 3 1 4 3 1 3 3 3 3 1 2 3 4 2 4 3 2 3 1 1 2 3 1 4 1
## [9649] 3 1 3 3 3 1 3 1 1 3 3 3 1 3 2 2 3 4 2 1 1 2 3 1 1 1 2 4 2 3 2 3 3 1 3 4
## [9685] 1 3 2 4 1 2 1 2 2 1 2 3 4 4 2 2 3 1 3 3 2 3 3 2 1 2 4 3 1 1 2 2 3 3 3 3
## [9721] 2 4 3 3 3 1 4 2 2 2 2 2 3 2 4 2 2 1 1 2 3 1 4 2 1 1 3 1 1 1 4 3 2 3 2 3
## [9757] 2 4 2 2 3 1 1 3 3 3 3 4 3 4 1 1 1 4 3 2 2 3 4 3 3 4 1 3 1 1 3 3 1 2 1 1
## [9793] 4 2 3 1 3 1 4 1 2 2 4 2 3 3 1 1 4 1 2 3 3 1 1 1 1 3 1 2 3 2 3 1 3 3 3 1
## [9829] 1 3 1 1 2 1 3 3 3 2 3 1 1 1 1 1 4 2 3 4 2 2 3 3 4 2 3 2 3 2 3 1 4 2 1 3
## [9865] 2 4 1 2 1 1 1 3 3 1 2 3 1 3 1 1 1 4 2 4 3 3 3 3 1 2 2 2 3 2 3 2 3 2 1 4
## [9901] 2 2 2 3 1 2 2 3 3 1 1 3 3 1 3 1 3 1 3 3 3 2 2 1 4 1 1 1 3 1 3 2 4 1 4 4
## [9937] 4 3 3 3 3 4 3 3 4 1 1 3 3 4 4 2 3 2 2 2 3 3 1 3 3 1 2 3 3 2 3 2 3 4 1 1
## [9973] 2 3 3 3 2 3 2 4 1 2 2 2 2 1 2 1 2 1 3 2 2 4 3 3 2 2 3 1 3 2 1 1 3 2 2 3
## [10009] 2 2 2 1 4 3 1 3 1 3 3 3 2 2 2 2 3 2 4 1 1 2 3 2 3 2 3 2 2 4 3 2 4 2 3 1
## [10045] 3 2 2 3 4 4 2 2 1 2 2 1 2 1 4 1 1 2 2 1 2 3 1 4 4 1 1 3 3 3 2 3 3 3 1 3
## [10081] 1 3 2 3 4 3 3 1 2 2 4 2 1 1 3 1 3 3 2 4 4 1 3 1 2 3 1 2 2 3 1 2 2 4 1 3
## [10117] 1 3 2 3 3 3 1 4 3 2 3 3 1 3 4 3 3 3 3 3 3 4 2 3 1 2 3 2 3 4 3 1 2 1 3 3
## [10153] 3 4 3 2 2 3 4 1 3 2 3 2 4 4 4 3 2 1 3 1 2 3 3 3 2 3 3 3 4 3 1 1 3 2 3 2
## [10189] 1 2 3 1 4 2 1 3 3 3 1 1 3 3 3 4 3 3 2 3 1 3 3 3 1 1 3 3 1 3 1 3 4 3 1 4
## [10225] 3 1 3 3 3 1 3 1 1 4 3 3 3 1 2 2 1 3 3 2 1 3 4 3 1 4 2 3 1 2 4 3 3 2 3 3
## [10261] 3 3 3 2 4 2 1 3 4 1 1 2 1 1 2 3 1 1 3 4 3 3 3 3 1 3 2 4 1 2 2 3 1 2 4 3
## [10297] 3 4 3 2 1 2 4 3 3 2 2 1 1 1 4 2 3 1 3 3 2 4 2 3 2 3 2 2 2 3 3 3 4 2 3 3
## [10333] 1 3 2 3 1 4 2 3 3 3 4 1 3 3 1 1 3 2 3 2 3 3 3 3 3 3 2 2 2 2 2 3 3 3 3 3
## [10369] 1 1 1 3 3 3 1 3 4 2 2 1 4 4 2 1 3 1 1 1 3 3 2 3 3 4 3 3 3 3 4 3 1 1 1 3
## [10405] 1 1 4 3 4 2 4 1 3 2 4 3 1 3 3 3 3 3 1 3 3 3 4 3 4 3 2 3 3 3 1 2 3 3 1 3
## [10441] 3 3 1 3 4 1 3 1 2 4 4 3 3 3 1 3 1 1 4 3 4 4 2 3 3 3 1 3 4 4 3 4 4 2 3 4
## [10477] 1 3 1 2 3 2 1 3 4 4 3 2 4 2 3 2 3 1 3 4 3 2 3 1 1 2 3 2 1 2 1 2 2 3 1 1
## [10513] 1 3 2 1 1 3 1 4 1 4 3 3 3 1 1 1 2 3 1 3 2 3 2 1 1 1 2 1 4 1 1 3 3 2 2 3
## [10549] 2 2 3 2 3 2 3 2 3 1 2 2 1 3 3 2 3 2 1 1 1 4 1 3 3 3 3 3 3 1 3 3 3 3 3 2
## [10585] 2 3 1 2 2 3 1 1 1 1 3 4 4 3 1 2 3 3 3 4 3 1 3 4 4 3 3 3 4 3 1 4 2 3 4 3
## [10621] 3 4 3 2 4 3 4 2 3 2 1 1 2 3 1 1 4 2 3 2 3 3 3 1 4 1 1 1 1 3 1 3 3 3 3 3
## [10657] 3 2 3 4 4 4 2 3 2 2 3 2 2 3 3 2 2 1 2 1 2 2 2 4 2 2 1 4 1 2 1 3 2 3 4 3
## [10693] 3 2 2 4 4 1 1 4 2 3 1 3 1 1 1 2 2 1 4 3 1 1 2 1 1 3 1 2 1 2 3 2 4 3 3 3
## [10729] 1 3 3 1 1 4 4 3 2 3 1 1 4 2 3 2 2 1 3 2 3 1 4 3 3 3 1 1 1 1 3 3 4 2 3 1
## [10765] 2 1 3 3 2 1 3 3 3 2 2 3 1 2 3 3 3 4 2 1 2 2 2 3 3 3 3 1 3 1 2 2 4 2 2 4
## [10801] 2 3 2 2 4 4 1 2 4 1 3 2 1 3 3 2 2 3 2 2 1 3 1 4 2 3 1 2 1 1 2 3 3 4 2 4
## [10837] 1 1 3 3 2 1 4 3 3 3 2 3 2 2 1 1 2 3 1 3 3 4 1 4 1 1 1 3 4 4 4 3 3 2 4 3
## [10873] 3 3 3 3 3 2 3 2 2 2 3 2 3 3 1 2 3 2 1 3 2 3 4 3 1 3 2 1 4 3 1 3 3 2 3 3
## [10909] 1 2 4 1 3 2 2 3 3 3 2 2 1 2 2 4 3 1 3 3 1 3 1 1 3 3 1 3 2 2 3 2 4 3 3 1
## [10945] 1 4 2 3 1 1 3 2 4 2 4 3 3 3 3 1 1 3 1 1 1 2 4 1 2 1 1 3 1 3 3 1 1 3 1 4
## [10981] 1 1 3 3 2 2 2 3 3 3 3 2 2 1 3 4 2 2 2 4 3 2 3 4 2 3 2 3 1 2 4 4 1 3 3 2
## [11017] 1 4 4 2 4 4 2 3 1 3 1 3 2 1 3 3 4 3 2 4 2 3 1 1 2 3 3 3 2 1 1 3 3 3 3 3
## [11053] 3 3 3 1 2 3 3 1 3 3 2 3 1 3 3 3 2 2 3 3 1 1 3 1 1 4 4 3 1 3 1 1 2 1 3 1
## [11089] 3 2 1 2 1 3 4 1 4 2 3 3 3 2 4 1 3 1 4 3 1 4 4 1 1 2 2 3 2 3 3 3 2 2 4 3
## [11125] 1 3 3 3 3 1 1 3 2 4 2 1 2 3 1 4 3 3 3 1 3 2 3 1 3 1 3 3 4 1 4 3 3 3 3 3
## [11161] 2 3 4 3 2 4 2 2 1 3 2 2 2 1 3 1 2 1 4 3 2 4 1 1 2 3 2 2 2 1 3 1 3 1 3 4
## [11197] 1 3 1 1 1 4 2 4 2 2 2 2 2 4 4 3 3 3 2 1 4 3 2 1 4 2 2 3 1 2 4 1 3 1 3 3
## [11233] 3 3 3 3 1 2 1 3 2 4 1 2 1 2 1 2 3 3 3 2 1 2 1 4 3 2 3 2 1 1 3 1 3 4 2 2
## [11269] 1 3 2 1 2 1 2 4 3 3 3 2 2 3 2 3 3 2 3 3 2 2 2 4 2 1 2 2 3 3 3 3 4 2 1 2
## [11305] 3 3 3 4 2 1 3 3 3 3 3 3 2 3 1 4 3 4 2 3 2 3 3 4 1 3 2 2 1 1 3 1 2 1 3 3
## [11341] 3 2 4 2 2 1 2 1 1 2 3 1 3 1 1 1 3 3 2 1 3 4 1 4 4 2 3 2 1 2 3 3 2 1 1 4
## [11377] 3 3 2 3 1 3 1 1 1 2 1 4 4 3 2 1 3 3 1 1 3 3 3 1 3 4 2 3 4 3 1 3 3 4 3 4
## [11413] 3 4 1 4 1 3 1 1 3 3 2 1 1 2 2 1 3 3 1 4 2 4 3 4 2 3 1 2 2 3 1 3 4 1 4 1
## [11449] 1 3 3 2 3 3 2 3 4 1 3 1 1 3 3 2 3 4 2 3 3 2 3 3 3 1 2 1 1 3 3 3 2 1 3 1
## [11485] 3 3 3 4 4 3 1 1 3 3 1 3 3 3 3 1 1 1 3 3 1 3 1 2 3 3 3 3 4 2 3 2 1 3 2 3
## [11521] 1 1 4 3 1 1 4 3 2 3 3 1 2 3 2 3 3 3 3 3 2 2 2 2 3 3 2 2 3 3 3 2 2 1 4 3
## [11557] 4 2 1 4 1 3 3 2 1 1 2 3 3 2 4 4 1 3 4 2 2 2 1 3 3 3 3 2 3 2 2 2 2 3 3 1
## [11593] 3 1 3 2 4 1 4 4 1 3 4 2 3 2 3 3 1 1 1 3 2 2 2 3 3 3 3 2 3 2 2 2 3 3 2 1
## [11629] 3 2 3 2 3 2 1 2 2 3 1 1 2 1 1 1 1 3 2 3 3 1 2 2 1 2 1 1 4 4 2 3 3 3 2 2
## [11665] 1 2 3 4 3 3 3 3 4 2 2 4 2 1 2 1 1 3 3 3 2 3 3 3 3 2 2 2 2 4 3 3 3 1 3 2
## [11701] 3 2 3 4 3 3 1 1 3 3 1 3 3 4 3 2 3 3 2 3 3 4 1 2 3 2 3 1 3 3 2 2 4 1 1 4
## [11737] 2 2 2 2 4 3 4 2 1 2 3 3 3 2 3 3 3 3 3 2 2 3 3 2 3 1 1 1 2 1 2 2 3 3 2 1
## [11773] 2 1 1 1 1 1 2 2 1 4 3 2 3 1 3 1 1 3 3 3 2 1 3 1 2 3 3 4 1 4 1 2 3 2 3 2
## [11809] 3 3 1 1 1 2 1 1 2 1 4 1 1 3 3 2 2 3 2 2 3 3 3 3 1 3 3 3 3 3 4 4 3 3 1 3
## [11845] 1 3 3 3 3 3 3 2 1 3 2 2 3 4 3 4 3 3 1 3 3 3 3 2 2 3 1 2 2 1 2 2 4 2 4 4
## [11881] 1 2 3 2 2 4 3 3 3 2 3 1 2 4 1 2 3 2 3 4 3 1 2 3 3 3 1 4 3 4 1 2 2 4 1 2
## [11917] 2 1 3 2 4 2 4 4 4 2 1 1 3 3 2 4 3 2 4 2 1 3 3 2 2 4 3 2 3 3 1 2 1 1 2 1
## [11953] 1 3 1 4 3 2 4 1 1 2 3 2 3 1 2 2 3 2 3 3 2 2 3 1 1 1 1 1 3 3 1 1 4 3 4 1
## [11989] 3 2 3 3 2 4 2 1 2 1 1 3 1 3 2 3 2 3 3 2 4 2 3 3 1 3 1 2 1 1 4 3 2 3 3 1
## [12025] 2 3 1 3 3 4 3 1 1 2 2 2 4 3 3 2 3 3 4 4 2 2 3 2 3 3 3 1 1 1 2 1 2 3 3 4
## [12061] 3 3 2 3 3 2 3 1 3 1 3 3 2 1 2 3 4 1 2 3 1 2 3 2 3 3 4 4 1 3 3 3 3 3 4 3
## [12097] 3 4 1 3 1 3 3 2 3 2 3 2 1 2 2 2 3 3 2 2 4 2 3 3 3 2 1 4 4 3 3 3 3 3 3 2
## [12133] 3 3 1 3 1 3 2 3 4 2 1 3 1 3 2 3 3 2 3 3 4 3 2 4 1 2 3 1 2 3 2 3 3 3 3 2
## [12169] 1 1 2 3 3 1 1 3 2 2 2 2 1 2 3 2 3 1 3 2 3 3 3 4 2 2 1 3 3 1 3 3 1 3 3 3
## [12205] 4 1 4 2 2 1 2 3 1 2 4 1 2 3 3 2 2 1 3 1 1 3 4 2 1 1 1 2 3 2 3 2 3 1 1 4
## [12241] 2 3 2 4 3 3 3 3 4 1 2 3 3 1 4 4 3 3 2 2 2 3 3 2 3 3 3 4 1 4 4 3 4 3 2 4
## [12277] 3 3 4 1 2 3 2 1 1 1 3 2 3 2 3 2 2 2 4 1 1 3 3 1 4 3 3 1 2 2 1 3 3 4 1 2
## [12313] 2 2 2 2 3 3 1 3 2 3 2 3 1 3 3 4 2 3 3 2 4 1 3 2 3 2 3 2 3 1 1 3 2 3 1 4
## [12349] 2 1 1 4 3 1 1 3 1 3 2 1 2 2 3 2 1 2 2 2 4 3 1 3 1 2 3 2 3 4 2 4 3 2 3 3
## [12385] 1 3 1 3 1 1 1 2 3 3 4 2 4 1 4 3 3 1 2 4 4 4 4 1 2 1 4 1 2 2 2 1 1 1 3 1
## [12421] 1 1 3 1 4 1 3 4 1 1 2 3 3 3 3 3 2 2 3 4 1 3 3 2 1 4 2 1 2 4 2 2 2 2 1 3
## [12457] 4 1 4 3 3 3 3 3 4 4 2 3 1 3 3 2 3 1 2 1 1 1 4 3 1 2 1 3 4 4 2 3 1 3 2 3
## [12493] 4 4 4 2 3 3 1 4 3 1 3 3 3 3 3 2 4 2 4 3 3 2 4 1 3 3 4 2 1 3 2 3 3 2 3 1
## [12529] 2 2 3 1 3 2 2 2 1 3 4 3 2 4 3 2 2 1 1 3 3 1 3 2 3 4 4 4 1 3 4 1 2 4 3 2
## [12565] 3 3 1 2 1 2 3 1 3 4 1 1 3 1 3 4 2 2 3 3 3 1 2 2 3 2 3 2 3 3 3 3 3 4 1 3
## [12601] 3 3 2 4 2 2 3 1 4 2 3 3 3 2 2 3 3 1 3 3 1 3 4 3 3 3 1 3 3 3 2 1 3 2 3 3
## [12637] 3 3 1 2 3 1 3 3 2 3 4 3 3 2 2 3 4 3 2 1 2 2 2 3 2 2 1 1 1 1 3 4 3 3 2 3
## [12673] 4 1 3 2 3 4 2 1 2 1 4 3 3 4 1 2 3 2 4 2 3 3 1 3 3 4 2 2 1 3 3 1 3 2 3 2
## [12709] 3 3 3 3 1 3 3 1 3 2 3 1 4 4 2 3 2 2 2 1 1 2 4 3 4 3 1 4 2 1 1 3 2 4 3 3
## [12745] 3 1 3 4 3 1 2 2 3 1 3 4 3 1 2 3 4 4 4 2 3 3 2 3 1 2 1 2 3 3 1 1 3 3 3 3
## [12781] 3 3 1 3 3 2 1 3 3 1 1 2 4 1 1 1 4 1 3 4 3 3 3 2 1 3 2 1 3 3 3 3 3 2 3 3
## [12817] 3 1 1 2 3 2 3 3 2 3 3 1 1 3 2 3 2 3 3 2 4 4 4 3 3 3 3 3 1 1 2 3 3 3 2 1
## [12853] 2 4 2 3 4 2 3 3 1 3 3 2 4 2 2 2 4 3 4 1 2 3 3 2 3 3 4 2 3 2 4 4 1 4 1 1
## [12889] 3 1 3 2 3 2 2 3 1 3 3 3 3 3 2 1 4 1 3 3 2 3 2 2 2 3 4 3 2 4 4 3 1 2 1 4
## [12925] 2 4 2 3 3 3 3 3 3 1 3 3 2 1 1 2 1 1 2 2 1 3 1 1 1 3 4 4 1 1 2 2 1 3 4 2
## [12961] 2 3 4 3 2 3 2 1 3 3 3 3 3 3 1 3 2 3 2 3 2 3 4 1 3 1 1 2 1 1 3 3 1 1 2 3
## [12997] 3 2 1 3 2 3 3 3 3 3 4 2 1 3 4 2 4 3 3 2 4 3 2 2 1 3 4 2 3 2 4 2 1 3 2 1
## [13033] 4 4 3 2 1 3 2 2 1 1 2 3 1 1 3 2 4 3 1 2 1 3 1 1 3 3 2 1 1 1 1 1 2 1 3 2
## [13069] 2 1 2 1 1 3 1 2 3 2 3 3 2 3 1 2 3 3 3 3 3 3 2 3 3 2 2 3 3 3 3 1 3 1 2 3
## [13105] 3 3 3 2 1 4 3 2 3 3 4 1 1 3 3 3 3 2 3 1 3 3 1 2 3 3 3 3 1 4 1 3 3 1 3 1
## [13141] 3 3 2 3 2 3 2 3 3 4 2 3 3 1 1 1 4 2 3 2 4 2 2 3 1 1 3 2 3 3 2 3 1 2 3 4
## [13177] 1 3 3 4 3 1 1 1 3 2 4 4 3 2 2 4 2 2 4 1 1 2 2 3 3 3 3 4 3 1 2 4 2 4 1 2
## [13213] 3 4 1 3 3 1 1 1 3 1 3 2 1 2 2 1 1 4 3 2 3 3 3 1 1 1 2 1 1 4 3 3 1 1 3 3
## [13249] 3 1 4 1 3 4 3 3 3 3 1 1 2 1 1 3 1 2 2 3 3 2 2 2 3 2 2 3 2 3 3 4 3 2 2 3
## [13285] 3 3 1 3 4 1 3 1 4 3 3 2 4 3 2 3 3 1 2 3 4 3 1 1 2 3 3 3 1 1 1 3 3 3 3 1
## [13321] 3 3 3 3 2 3 4 1 2 3 3 3 1 4 2 4 1 1 2 1 3 4 3 2 4 2 3 1 2 2 1 3 3 2 2 1
## [13357] 3 2 2 2 4 3 3 3 3 3 3 1 3 3 3 1 3 3 3 3 2 4 1 1 1 2 2 3 2 4 2 1 2 3 1 3
## [13393] 1 2 1 3 3 1 3 3 4 3 3 3 4 1 3 3 1 3 1 3 1 2 1 2 3 2 3 4 2 3 3 3 3 4 2 2
## [13429] 1 3 4 1 2 1 1 3 1 3 1 1 2 3 1 4 2 3 3 3 1 2 1 3 1 1 1 4 3 3 1 3 3 1 4 4
## [13465] 3 2 1 1 3 1 3 4 1 4 3 3 2 3 2 1 3 1 1 2 4 3 3 2 3 3 2 3 3 3 2 1 2 2 3 3
## [13501] 4 2 4 3 4 4 2 4 2 3 3 4 1 2 3 3 1 4 3 3 1 4 4 4 4 2 3 3 2 1 2 1 3 3 4 2
## [13537] 4 1 4 2 2 3 1 3 4 2 2 2 1 4 2 4 1 1 1 2 2 3 1 4 4 3 4 1 2 3 1 1 3 2 4 3
## [13573] 2 3 3 3 3 4 2 2 1 2 3 3 2 3 3 1 3 2 3 2 3 3 2 3 2 1 2 3 1 3 4 3 4 1 2 2
## [13609] 1 4 1 1 1 3 1 4 1 4 1 4 3 2 2 2 4 2 2 2 3 3 4 4 3 2 4 3 2 1 3 4 1 3 3 1
## [13645] 3 1 1 1 2 1 2 2 2 3 3 3 2 4 1 3 4 3 3 4 2 2 2 3 1 1 2 2 1 3 1 2 1 1 1 1
## [13681] 1 2 3 1 3 3 1 3 2 3 4 2 2 3 2 3 3 3 1 4 2 2 1 1 1 4 1 2 3 1 2 3 1 2 1 3
## [13717] 2 3 3 1 2 1 2 1 2 2 4 3 3 4 1 3 3 2 3 2 2 1 2 1 3 2 2 1 3 1 3 3 3 1 1 1
## [13753] 2 3 1 2 3 1 2 4 3 1 1 2 1 3 3 2 1 3 2 1 3 3 3 2 2 3 3 4 3 3 3 3 4 1 3 3
## [13789] 1 1 2 3 2 1 3 1 1 2 4 1 1 1 2 3 3 3 3 3 3 2 2 1 3 3 3 3 1 3 2 2 2 4 2 3
## [13825] 3 4 3 1 3 1 4 3 2 3 3 1 2 2 1 2 3 3 4 3 1 2 2 1 1 4 4 1 3 3 3 2 2 3 3 3
## [13861] 2 1 3 2 3 2 4 2 1 4 2 1 1 4 2 4 1 2 2 4 3 2 2 3 1 1 4 1 2 2 2 1 1 4 3 2
## [13897] 3 2 3 1 4 1 2 3 1 2 2 3 1 2 3 1 3 3 3 3 1 1 1 3 1 1 3 4 3 2 2 1 1 3 3 1
## [13933] 1 3 2 3 1 1 1 3 4 4 2 3 3 4 3 2 4 2 2 1 3 1 3 3 3 1 1 2 1 1 3 3 4 2 2 3
## [13969] 1 1 3 3 4 4 2 3 1 3 3 3 3 1 3 3 3 2 4 2 3 1 1 1 2 1 3 3 2 2 1 1 3 2 3 3
## [14005] 4 1 2 1 3 4 4 4 2 1 1 3 2 4 1 2 3 1 4 2 3 3 2 3 3 3 2 2 1 3 3 3 1 1 4 2
## [14041] 1 3 2 1 2 1 3 1 3 2 4 4 2 3 2 1 2 4 1 3 1 1 1 3 2 4 3 2 2 1 2 1 4 1 1 3
## [14077] 2 3 1 3 2 3 3 2 3 1 4 2 3 1 4 1 4 3 3 3 3 3 4 1 3 2 4 3 2 2 4 3 2 1 3 4
## [14113] 2 4 1 1 2 2 1 3 4 1 4 3 2 2 2 3 3 3 1 3 3 1 3 4 4 3 2 2 1 4 3 3 4 2 1 4
## [14149] 1 4 2 2 4 3 3 1 3 3 2 2 4 1 2 2 2 3 3 3 1 3 2 3 3 4 3 3 4 3 1 2 3 3 2 2
## [14185] 3 2 4 3 4 2 3 3 2 1 1 2 2 1 3 1 2 3 3 3 1 2 3 1 3 1 2 2 3 2 3 2 3 1 1 3
## [14221] 3 1 1 2 3 1 3 1 2 2 3 3 4 1 2 2 2 3 4 3 3 3 4 2 2 4 1 4 2 4 3 1 2 3 3 3
## [14257] 2 3 1 3 1 1 1 1 1 2 3 2 3 3 4 3 3 4 1 2 3 3 3 3 1 3 3 2 1 3 3 3 4 4 3 2
## [14293] 4 1 4 3 4 1 1 2 4 3 4 3 1 3 1 2 3 3 3 1 2 2 1 3 1 1 3 2 2 3 3 2 3 2 3 1
## [14329] 2 2 3 1 3 2 3 2 3 3 1 2 2 2 1 3 2 4 2 2 3 3 2 1 3 2 4 1 3 3 1 4 2 2 1 3
## [14365] 3 1 3 3 4 2 3 3 2 3 3 1 3 2 1 2 1 1 4 3 4 4 2 3 1 2 3 4 3 2 3 2 2 1 1 1
## [14401] 2 3 3 3 1 1 3 4 1 3 2 4 2 2 2 3 4 3 4 1 1 2 3 2 1 4 4 2 4 3 2 4 1 3 2 2
## [14437] 3 3 2 2 3 1 3 1 3 1 4 1 2 2 1 1 3 3 2 3 3 4 3 1 2 3 3 2 1 2 3 3 3 2 3 1
## [14473] 3 1 3 3 3 1 2 2 3 3 3 3 1 1 1 3 3 2 2 3 4 1 3 3 1 3 3 3 1 2 2 4 3 2 3 3
## [14509] 3 1 3 3 3 3 2 2 3 3 2 3 3 3 4 2 2 3 4 4 3 2 2 3 2 3 3 2 3 4 4 2 3 1 3 1
## [14545] 3 1 1 2 4 1 3 1 2 1 2 4 1 3 4 1 3 2 1 3 4 3 1 3 3 1 2 1 4 2 1 4 1 3 2 3
## [14581] 3 1 4 2 1 2 4 2 4 4 3 1 3 3 4 1 3 3 2 3 3 1 3 3 1 3 2 3 3 1 3 2 4 2 4 3
## [14617] 2 1 3 3 4 2 2 3 1 4 1 1 1 2 1 2 2 3 3 2 2 3 3 4 3 3 1 4 1 4 3 1 2 1 2 3
## [14653] 3 2 2 1 3 4 2 2 3 4 3 4 2 2 4 2 1 2 2 1 2 1 2 3 1 4 3 1 3 2 2 1 2 3 3 1
## [14689] 4 3 2 4 2 3 4 4 2 2 1 3 1 1 3 3 2 3 3 1 1 3 1 4 3 3 3 3 1 3 4 3 3 1 4 3
## [14725] 1 2 4 4 2 3 3 2 4 1 2 1 3 1 2 3 4 2 2 1 2 1 1 4 2 3 1 2 4 2 3 4 3 4 4 3
## [14761] 2 1 2 3 4 3 3 3 3 3 4 4 3 3 3 1 1 4 1 2 1 3 3 3 2 1 2 1 3 3 3 3 1 3 4 3
## [14797] 3 1 3 2 4 3 2 2 3 2 4 3 3 3 3 3 3 2 3 1 2 2 1 1 2 1 2 3 3 3 4 2 3 3 3 4
## [14833] 2 3 2 4 1 4 3 3 2 2 1 1 2 3 3 2 3 4 3 3 1 2 2 3 3 2 4 2 1 2 4 1 1 2 3 3
## [14869] 3 2 3 4 4 3 2 1 2 2 1 1 2 3 1 1 3 1 4 2 3 2 4 2 2 4 3 3 1 1 1 1 3 2 3 2
## [14905] 3 4 1 3 1 4 1 1 2 2 2 2 3 3 3 3 1 1 3 1 4 1 1 1 3 3 3 3 2 1 1 4 4 1 4 2
## [14941] 4 2 3 3 2 4 1 2 3 3 2 1 3 1 3 1 1 2 1 1 4 3 1 3 2 3 3 4 3 3 3 1 1 3 1 3
## [14977] 3 2 3 3 3 3 2 2 4 4 4 4 1 3 2 2 3 2 2 2 2 3 3 3 2 2 2 1 2 3 3 3 1 3 2 2
## [15013] 4 2 3 1 1 4 3 3 3 3 1 4 3 2 3 2 1 3 4 3 2 3 3 1 3 3 3 1 1 4 3 2 4 3 2 3
## [15049] 3 2 2 1 3 3 2 2 1 2 2 3 2 1 3 3 3 3 2 3 1 2 3 2 1 1 4 3 2 2 2 1 3 3 2 3
## [15085] 1 2 3 3 2 1 3 1 3 3 1 1 2 2 4 3 3 3 4 1 4 1 2 1 3 2 1 3 1 3 4 3 2 1 2 3
## [15121] 3 1 2 1 2 1 1 1 3 4 4 1 2 3 3 3 2 3 2 3 1 1 4 2 1 2 2 3 2 1 1 1 2 4 4 2
## [15157] 4 4 4 1 4 1 2 4 3 4 4 4 2 3 1 2 3 3 2 3 1 2 3 3 2 4 3 2 3 3 3 3 1 1 1 1
## [15193] 4 1 2 2 3 2 3 3 2 3 4 1 1 3 3 1 4 3 3 1 4 2 2 3 3 2 3 3 2 1 4 4 3 1 1 1
## [15229] 3 3 3 1 3 4 2 1 3 3 1 3 4 3 3 3 1 3 2 3 1 1 2 3 3 3 1 3 1 1 3 2 2 3 3 2
## [15265] 3 1 1 1 4 2 2 3 3 4 3 2 2 3 2 3 4 2 3 3 1 3 2 4 3 3 2 3 3 1 1 1 2 3 3 4
## [15301] 1 4 1 2 3 3 4 1 2 2 1 1 2 3 1 3 4 3 2 1 4 3 3 1 1 3 3 2 2 4 3 3 3 3 2 4
## [15337] 2 3 1 2 3 2 1 3 2 2 3 1 2 3 4 3 4 1 2 3 3 2 3 2 4 2 2 1 4 3 3 4 2 3 3 3
## [15373] 4 3 1 3 3 3 1 3 1 1 3 3 3 2 3 1 3 3 4 1 2 3 3 2 3 2 2 3 2 2 2 3 1 2 3 1
## [15409] 3 1 1 1 1 3 2 1 2 3 1 4 4 2 1 3 3 3 3 2 1 3 1 4 3 3 1 3 3 3 4 3 3 3 3 3
## [15445] 4 2 2 1 3 1 2 3 1 3 2 3 3 1 3 3 3 1 1 3 1 1 1 4 2 2 1 3 3 2 3 2 3 2 1 4
## [15481] 4 2 3 2 4 4 3 1 4 1 4 1 1 3 4 3 2 3 2 3 1 3 3 1 2 1 3 3 3 2 3 1 3 2 1 3
## [15517] 4 4 1 4 3 2 1 3 4 3 1 2 3 4 4 4 3 4 3 2 1 2 3 3 3 1 1 2 3 1 2 2 3 2 3 4
## [15553] 1 4 2 1 1 3 1 1 1 4 1 1 2 2 2 4 2 2 2 3 4 2 2 2 3 3 3 3 4 3 3 1 1 1 2 3
## [15589] 2 3 4 2 1 2 2 2 4 3 2 2 4 1 3 2 1 2 3 2 4 2 3 2 2 2 1 1 1 3 2 2 2 1 1 4
## [15625] 3 3 2 1 2 3 1 1 3 3 1 4 4 2 2 1 4 4 4 4 2 1 4 3 1 3 3 1 3 4 2 2 2 3 3 2
## [15661] 4 3 3 1 3 1 3 3 3 3 2 3 1 1 2 1 3 2 1 3 4 1 2 3 2 3 3 1 1 3 2 3 3 2 4 2
## [15697] 2 3 3 3 2 2 1 1 1 3 3 2 3 3 3 4 1 3 1 3 3 4 2 3 3 3 3 2 3 3 4 3 1 4 1 2
## [15733] 3 1 2 3 3 1 4 1 3 1 4 4 4 2 1 3 2 1 3 3 2 1 3 3 2 3 1 1 3 1 3 3 3 2 1 3
## [15769] 2 1 3 1 3 1 1 1 1 3 2 4 1 2 3 3 2 1 1 3 2 3 1 2 2 2 3 3 4 3 2 4 4 3 1 2
## [15805] 1 3 3 3 1 1 2 1 2 3 1 1 1 1 3 2 4 3 3 4 1 3 3 2 3 1 3 2 2 3 1 3 3 4 3 3
## [15841] 1 3 2 1 2 1 3 3 3 2 3 3 1 3 1 1 3 2 1 2 2 4 4 2 2 1 4 3 1 2 3 3 4 4 3 4
## [15877] 1 4 3 1 3 1 3 1 1 1 2 3 2 3 3 3 3 3 1 1 3 3 4 4 4 3 4 3 2 2 3 1 3 3 2 3
## [15913] 3 3 2 1 3 2 3 1 2 3 3 4 3 1 1 3 1 2 2 3 3 1 4 2 4 1 2 1 3 2 1 3 1 2 1 2
## [15949] 3 3 2 4 1 1 3 2 4 1 3 3 1 3 1 1 4 1 1 2 1 2 3 4 3 3 2 2 1 4 1 1 4 4 2 1
## [15985] 3 2 3 3 1 2 3 4 3 3 2 3 3 2 2 2 4 1 3 3 3 1 4 1 1 2 3 2 3 4 3 3 2 2 2 4
## [16021] 3 2 1 3 2 1 3 3 4 4 3 3 3 4 3 2 3 1 2 3 2 3 3 3 3 2 4 2 2 3 1 3 3 2 3 4
## [16057] 3 1 2 3 3 4 1 3 3 4 2 3 2 1 3 4 2 3 3 1 2 4 1 3 2 3 1 3 2 3 3 1 1 3 2 1
## [16093] 3 1 3 1 3 3 2 3 3 2 4 4 2 1 2 1 1 3 4 3 1 2 4 1 3 3 2 3 1 4 2 3 3 2 2 2
## [16129] 3 3 3 3 1 4 3 3 2 1 4 1 3 3 2 1 3 3 1 2 1 3 1 3 2 1 3 1 1 2 3 1 3 4 2 4
## [16165] 3 1 1 1 1 3 3 2 2 3 3 3 3 3 1 2 2 4 3 2 4 1 2 2 2 3 4 3 3 2 1 3 3 3 3 4
## [16201] 3 3 2 2 2 1 2 2 1 3 3 3 1 3 3 1 2 4 3 1 3 3 2 3 1 3 4 1 1 1 3 2 1 1 1 4
## [16237] 2 4 4 1 2 1 2 1 2 1 4 3 4 3 1 3 3 2 3 3 1 2 1 3 2 3 2 3 3 2 3 2 3 3 3 2
## [16273] 3 2 1 3 3 3 3 2 2 4 3 2 2 3 1 1 3 2 3 1 3 3 2 1 1 1 1 3 2 2 1 3 3 2 1 3
## [16309] 2 3 2 3 1 3 4 3 3 3 3 1 3 2 2 2 3 3 4 4 1 3 3 1 1 2 3 3 3 3 1 3 4 2 3 2
## [16345] 1 1 3 2 2 1 3 3 1 1 3 3 4 2 2 1 1 3 3 3 3 1 2 4 3 2 3 2 2 1 3 1 3 2 4 4
## [16381] 4 1 3 3 2 2 3 1 2 3 2 2 1 2 1 1 2 3 2 3 3 3 2 3 2 2 2 4 3 3 3 1 2 3 4 2
## [16417] 2 2 4 3 3 4 2 2 2 4 3 3 2 3 3 4 1 2 4 3 2 3 1 2 3 1 2 3 1 4 4 3 1 2 3 3
## [16453] 4 2 2 1 3 2 3 4 1 2 4 3 3 2 4 3 3 1 3 2 1 2 3 4 1 4 4 1 2 3 4 3 3 3 3 2
## [16489] 2 2 1 3 2 1 1 3 2 2 2 1 4 3 1 2 3 4 3 3 4 1 2 3 3 3 3 2 2 1 1 3 1 3 2 1
## [16525] 4 4 4 3 3 2 1 3 1 1 2 1 3 3 1 4 3 2 1 2 2 4 1 3 4 3 4 1 2 1 3 1 2 1 4 1
## [16561] 1 1 2 3 1 4 3 2 2 3 3 1 1 2 4 1 3 2 3 4 2 4 4 1 2 3 2 4 3 1 2 2 2 2 1 4
## [16597] 3 1 2 3 2 3 1 1 4 4 2 4 3 3 1 2 3 1 2 3 2 3 2 2 3 3 4 4 2 2 2 1 2 3 3 3
## [16633] 3 2 3 3 3 2 1 3 2 2 3 3 1 4 2 2 2 3 3 1 3 3 2 3 4 2 2 4 3 3 4 3 3 1 1 2
## [16669] 3 1 2 2 2 3 3 3 3 3 4 3 3 1 3 1 2 3 3 3 4 3 4 1 2 3 3 1 1 3 3 1 2 3 3 2
## [16705] 3 2 4 1 2 4 2 1 3 2 3 4 2 2 1 3 1 1 1 4 3 2 3 3 3 3 2 3 3 1 2 3 2 3 3 2
## [16741] 2 2 2 2 3 3 3 2 3 4 1 3 1 3 2 1 1 4 3 1 4 3 2 3 1 2 1 3 2 3 3 1 1 3 1 3
## [16777] 3 3 4 1 2 4 2 2 1 1 3 2 4 3 1 2 1 1 2 4 4 3 3 4 2 3 4 4 3 3 2 1 3 2 3 2
## [16813] 3 3 1 2 3 2 1 4 1 3 3 1 2 3 1 1 1 3 1 4 1 3 3 2 3 1 1 1 1 3 2 2 3 3 1 2
## [16849] 3 2 1 1 2 4 4 1 2 3 4 2 2 3 1 3 1 2 2 1 3 2 3 3 1 1 3 3 2 3 3 2 3 2 4 3
## [16885] 2 3 1 3 3 3 2 3 3 2 1 3 3 2 2 4 1 1 1 2 3 3 1 3 3 1 2 2 3 4 1 2 2 3 4 3
## [16921] 3 2 2 2 2 2 3 2 3 3 4 4 3 1 4 3 3 1 2 2 2 2 4 2 4 4 3 3 3 3 1 2 3 3 4 3
## [16957] 3 3 1 2 1 3 3 3 1 2 3 3 2 3 1 1 2 1 2 3 1 2 3 2 2 1 4 3 1 1 4 4 3 4 4 2
## [16993] 3 3 3 3 1 3 2 1 3 3 2 2 1 4 2 1 1 1 3 3 2 3 1 2 1 1 1 1 2 2 3 2 2 1 4 3
## [17029] 4 1 1 3 2 4 2 3 2 3 4 2 1 3 1 2 1 2 3 3 3 3 2 1 2 2 1 3 1 1 3 1 4 2 3 1
## [17065] 3 2 2 2 2 3 3 1 3 3 3 1 3 2 3 3 3 2 3 2 3 2 3 3 3 3 2 3 3 2 2 4 4 3 2 4
## [17101] 3 1 2 2 3 2 3 4 1 2 1 4 2 1 4 1 3 3 4 1 2 3 3 1 3 1 2 1 1 2 3 3 3 4 2 3
## [17137] 2 2 4 3 3 3 2 3 3 2 4 4 3 3 3 2 1 1 3 2 3 3 3 2 3 3 2 1 3 1 3 2 4 2 3 3
## [17173] 3 2 3 3 3 2 4 3 3 2 1 2 3 3 3 3 3 3 3 4 1 2 3 3 4 4 3 3 3 3 2 3 2 4 3 3
## [17209] 3 3 3 2 1 2 2 1 3 1 4 3 1 4 2 4 4 1 3 4 3 2 1 2 2 3 4 1 3 1 3 4 3 1 1 3
## [17245] 4 2 3 4 2 3 4 3 4 2 3 2 4 1 2 3 3 3 3 3 3 1 3 2 4 3 4 3 2 2 4 3 2 3 1 3
## [17281] 2 3 3 2 2 2 3 2 1 1 4 1 2 2 3 2 4 2 3 3 3 2 3 2 2 1 1 4 4 2 3 4 1 2 3 1
## [17317] 2 3 2 1 1 4 3 3 3 3 3 4 1 3 1 2 2 3 3 1 3 3 1 1 3 1 2 2 2 2 2 2 4 2 4 3
## [17353] 4 2 3 4 1 3 3 2 3 3 3 3 3 1 3 4 1 2 1 1 3 1 3 3 3 1 2 3 3 2 3 3 1 4 3 3
## [17389] 3 3 4 1 1 1 3 3 3 3 3 1 2 2 3 2 3 3 1 4 2 2 1 3 4 3 1 3 3 3 4 2 1 4 3 3
## [17425] 4 4 2 3 3 4 4 1 2 2 1 4 4 3 3 3 2 3 1 3 4 3 2 3 3 4 4 3 2 3 3 2 4 3 1 3
## [17461] 4 3 2 3 2 3 1 3 1 1 3 3 3 1 1 3 2 2 2 1 3 3 1 2 3 1 3 3 2 3 3 3 2 2 3 2
## [17497] 4 3 1 4 2 1 3 4 1 3 1 3 2 2 4 3 3 3 2 1 3 1 2 3 3 2 1 3 4 2 2 4 1 1 3 3
## [17533] 2 1 3 3 2 3 2 1 2 3 2 2 3 2 3 3 2 3 1 1 4 3 3 3 3 4 3 1 3 3 3 3 3 4 1 1
## [17569] 1 1 3 1 2 2 4 3 3 3 2 3 3 1 4 3 4 1 1 2 2 1 3 2 4 3 2 1 4 4 1 3 4 3 3 2
## [17605] 3 3 1 3 2 4 4 4 3 3 3 1 1 2 2 4 4 2 2 1 3 4 3 3 4 4 2 3 3 2 2 3 1 3 1 3
## [17641] 3 3 3 1 2 3 1 1 1 3 1 3 4 1 3 1 1 1 2 2 3 1 2 2 4 2 3 2 1 1 2 2 4 3 1 3
## [17677] 2 3 3 1 3 3 1 3 3 3 1 1 3 2 3 2 1 2 2 1 2 3 3 1 1 3 4 3 2 4 1 1 2 3 1 3
## [17713] 1 2 1 2 2 3 1 2 2 2 3 1 2 4 3 1 3 2 3 1 2 2 1 2 4 1 1 4 3 2 3 3 4 3 4 3
## [17749] 3 2 4 1 2 4 1 2 2 3 4 1 3 2 1 1 2 3 2 1 3 3 4 3 1 3 2 3 2 1 2 3 1 2 3 3
## [17785] 1 3 3 1 2 1 1 4 2 1 1 3 3 1 3 2 4 1 3 3 3 2 3 4 3 1 3 3 3 3 3 4 2 3 1 3
## [17821] 3 1 3 1 4 3 2 2 3 1 1 2 1 3 2 1 3 2 4 2 1 3 3 2 3 1 3 3 2 4 3 1 1 3 2 1
## [17857] 1 2 3 4 2 3 1 1 1 4 3 3 3 1 3 3 3 2 3 4 3 4 1 3 2 3 2 4 2 2 2 3 3 4 2 2
## [17893] 4 3 1 2 3 1 1 3 2 1 3 3 3 3 4 4 2 3 3 2 2 1 2 2 3 2 4 1 2 1 3 4 3 2 2 4
## [17929] 2 4 1 2 1 2 3 2 3 3 3 3 3 2 3 3 2 2 3 1 1 3 4 2 3 4 1 2 2 1 3 1 2 1 3 3
## [17965] 4 1 3 4 1 3 3 1 1 1 4 2 2 4 1 3 2 1 3 4 3 3 2 1 2 3 3 2 4 2 1 1 3 1 3 1
## [18001] 3 3 1 3 1 2 1 2 1 1 2 2 1 4 2 1 2 3 3 2 2 3 1 2 2 1 4 1 3 2 2 4 1 3 2 3
## [18037] 2 3 1 4 1 1 2 1 3 3 3 3 2 1 3 2 1 3 1 2 2 3 3 2 1 2 2 3 4 1 3 2 3 2 4 2
## [18073] 1 4 1 1 4 1 3 1 3 1 1 2 1 1 3 3 3 1 1 1 3 2 2 4 3 1 3 4 1 3 4 1 1 4 3 3
## [18109] 2 1 3 1 1 1 1 2 2 3 2 2 2 1 2 1 2 2 2 2 3 3 2 4 1 2 3 2 3 2 1 2 2 1 2 3
## [18145] 2 3 3 2 2 1 3 3 3 3 3 3 1 2 1 3 2 3 3 3 3 3 1 1 3 4 2 3 2 3 3 1 3 3 3 1
## [18181] 1 1 1 3 3 3 2 2 3 4 3 4 2 2 3 1 1 1 3 2 1 1 3 1 2 3 1 3 2 2 3 3 2 1 3 3
## [18217] 3 4 3 2 1 2 1 3 1 2 3 3 3 2 2 2 3 3 1 2 1 3 2 4 4 1 2 1 1 1 3 3 3 1 1 2
## [18253] 3 3 4 1 1 3 2 4 2 3 1 4 4 1 1 2 2 3 3 1 4 4 3 3 3 1 3 2 3 1 3 1 3 3 3 4
## [18289] 2 1 3 1 3 2 1 4 3 2 1 4 3 1 3 2 3 3 3 1 4 3 1 1 1 2 3 3 3 3 1 2 3 3 3 3
## [18325] 4 4 2 4 3 1 3 2 1 3 3 2 2 3 4 2 1 3 4 3 3 1 3 4 1 3 3 1 4 3 3 3 1 3 2 4
## [18361] 3 2 3 1 2 3 1 3 1 1 1 2 3 2 1 4 1 3 3 3 3 2 3 1 1 1 3 3 2 2 4 3 1 2 2 3
## [18397] 1 1 2 2 2 4 1 1 1 2 2 2 2 1 2 3 1 1 3 1 3 3 3 1 1 2 3 2 3 1 2 3 3 1 1 4
## [18433] 1 1 1 3 3 3 3 4 1 3 3 3 2 3 3 1 4 3 3 3 2 3 3 2 2 2 1 1 1 2 3 2 3 1 4 3
## [18469] 1 1 4 2 2 3 3 2 1 2 3 3 2 3 3 3 1 1 1 2 3 1 4 1 3 4 1 1 4 1 2 2 2 1 3 2
## [18505] 1 3 3 1 2 2 1 4 3 2 2 1 3 1 3 3 3 2 1 3 3 2 3 1 3 2 1 1 1 2 3 1 2 3 3 1
## [18541] 2 1 3 3 3 2 2 3 4 3 1 1 2 2 2 3 4 1 4 3 1 3 3 3 2 2 2 2 2 3 2 2 2 1 3 1
## [18577] 4 2 1 3 3 4 2 2 4 1 2 3 3 3 3 3 4 3 2 3 3 3 3 1 1 1 1 2 3 2 4 2 4 3 1 4
## [18613] 1 3 3 3 2 3 2 3 3 3 3 1 1 3 3 1 3 2 1 2 1 1 1 2 4 4 3 1 3 2 4 2 2 3 2 2
## [18649] 3 1 2 1 2 3 4 2 4 1 4 3 3 3 2 4 3 1 2 1 3 1 4 3 2 3 4 1 3 2 2 3 3 3 4 3
## [18685] 3 2 3 3 3 4 2 1 4 4 1 2 1 1 2 1 3 3 2 1 4 2 2 3 3 3 2 3 3 3 1 2 3 3 3 2
## [18721] 3 1 3 1 2 3 1 1 2 1 4 2 2 2 3 2 3 4 3 3 3 1 3 4 2 1 2 3 3 4 2 2 4 3 3 1
## [18757] 4 4 1 2 3 4 2 3 4 2 3 1 3 4 1 3 3 3 4 3 2 1 3 3 4 2 2 1 1 2 1 3 1 4 4 1
## [18793] 2 2 4 3 4 4 3 3 4 2 4 1 1 4 2 3 3 3 4 3 1 4 3 2 3 3 1 3 1 3 1 2 1 3 2 3
## [18829] 4 4 3 3 2 1 1 3 1 3 2 3 3 3 3 3 3 1 2 4 1 3 1 2 2 1 1 3 2 4 1 3 3 3 3 3
## [18865] 2 1 3 2 2 2 3 3 2 4 2 3 2 2 3 3 3 3 3 1 4 3 2 1 4 3 3 1 3 2 2 3 3 2 2 3
## [18901] 4 3 2 2 4 4 4 3 2 3 2 3 1 2 1 3 1 2 1 1 3 2 3 1 1 3 1 3 2 2 2 3 1 2 4 1
## [18937] 1 4 3 1 3 3 1 2 3 2 3 1 3 3 4 1 3 3 1 2 4 3 3 3 1 1 3 1 2 1 3 3 2 4 3 4
## [18973] 3 4 3 4 2 1 1 1 3 2 1 4 2 2 4 3 1 1 4 2 2 3 3 1 3 4 2 4 3 4 3 3 3 3 4 2
## [19009] 1 2 3 2 3 1 4 1 4 2 4 3 4 3 3 4 4 2 3 1 4 3 4 2 1 1 2 3 3 2 4 1 3 2 3 3
## [19045] 1 4 2 3 1 2 3 2 1 2 2 2 1 1 3 3 3 2 3 3 3 3 3 3 2 3 3 1 3 1 1 1 1 1 3 2
## [19081] 3 1 3 1 3 3 1 3 1 4 3 3 2 1 3 1 2 4 3 1 2 3 3 1 2 2 1 2 3 4 3 3 3 2 3 3
## [19117] 1 4 3 1 3 1 3 4 2 1 2 3 1 4 3 3 3 1 3 3 1 3 4 2 3 3 3 2 2 1 2 1 2 1 2 3
## [19153] 1 2 3 1 3 3 3 3 3 2 2 3 3 4 2 4 2 2 3 3 1 3 3 4 3 2 2 3 1 2 3 2 2 3 2 2
## [19189] 1 2 1 1 4 3 3 1 3 3 3 2 1 1 3 1 1 3 2 1 1 1 1 1 3 4 3 4 4 2 3 2 3 2 3 1
## [19225] 3 3 3 3 3 3 2 1 1 4 4 1 3 4 2 4 3 3 3 1 2 3 3 3 1 2 3 4 2 3 3 2 1 3 3 2
## [19261] 3 2 3 3 4 4 3 4 1 2 3 3 1 4 1 3 3 1 3 2 1 3 3 2 2 2 4 4 1 1 3 1 3 1 3 3
## [19297] 2 3 2 2 4 1 1 2 3 2 3 4 2 2 2 2 3 3 1 2 3 4 3 2 4 3 2 2 3 2 1 3 4 3 3 3
## [19333] 1 3 3 3 4 2 1 2 1 3 4 2 2 3 2 3 3 3 1 3 1 3 3 1 1 2 3 3 4 3 1 2 3 3 3 4
## [19369] 2 3 2 1 2 1 1 2 1 2 3 2 2 1 1 4 3 2 4 2 3 3 4 1 1 4 1 1 2 2 3 3 3 2 4 2
## [19405] 1 2 3 1 3 2 3 1 3 3 3 1 3 2 1 1 1 3 2 3 1 3 1 1 4 3 3 3 3 3 1 2 4 4 1 1
## [19441] 4 3 1 3 3 2 4 3 2 2 2 3 4 3 3 1 3 3 2 3 3 3 2 3 3 3 2 3 2 2 4 2 2 2 1 3
## [19477] 2 3 2 2 2 1 3 2 3 4 4 1 1 3 3 3 3 3 3 2 2 2 3 3 3 3 4 1 4 3 3 1 3 4 3 3
## [19513] 3 2 2 3 3 3 3 3 2 3 2 3 2 2 3 1 3 2 1 1 2 1 4 4 2 3 2 1 2 2 3 2 4 1 3 4
## [19549] 3 1 2 3 2 4 1 3 2 2 2 1 3 2 3 2 2 3 1 2 1 2 1 3 3 3 3 3 3 3 4 1 4 3 1 3
## [19585] 3 3 3 3 3 1 3 1 4 4 3 3 3 1 3 1 2 2 3 1 2 4 2 3 4 1 3 1 2 4 2 4 4 3 3 4
## [19621] 3 4 2 3 3 1 3 2 1 3 4 3 4 2 2 3 4 3 1 3 3 1 2 1 3 2 2 2 1 1 4 2 2 1 3 4
## [19657] 2 3 1 3 2 4 3 3 3 2 1 3 2 2 1 1 4 1 1 2 3 1 2 4 4 1 3 4 1 3 2 3 2 1 1 3
## [19693] 3 1 2 4 1 3 4 3 1 2 2 3 2 1 1 3 2 2 2 2 1 3 3 2 2 3 3 2 4 3 1 1 3 2 2 4
## [19729] 3 2 4 1 2 1 1 2 2 1 3 1 4 4 2 3 3 1 3 3 2 1 4 3 4 4 1 1 1 4 2 2 2 4 3 2
## [19765] 2 1 1 1 1 4 1 3 3 1 2 2 2 1 3 4 3 3 1 1 4 1 3 3 2 1 1 1 3 4 2 1 3 4 2 4
## [19801] 2 2 1 2 1 3 3 3 2 3 1 4 4 3 3 3 3 3 1 1 3 3 3 3 2 2 3 1 2 2 3 3 3 2 4 3
## [19837] 1 3 1 1 3 3 3 2 3 1 2 3 3 1 4 1 3 4 3 2 1 3 3 4 3 1 2 2 2 3 3 4 2 3 2 1
## [19873] 3 3 3 1 1 3 4 2 3 1 2 4 3 2 1 3 2 3 4 3 1 3 2 4 1 3 1 4 2 4 2 2 1 4 2 3
## [19909] 2 1 2 1 2 1 4 2 3 3 1 1 1 3 3 2 2 3 3 2 2 3 3 2 1 3 4 1 3 4 3 2 3 1 1 2
## [19945] 2 2 3 2 4 2 3 2 4 1 3 3 2 3 2 3 1 1 3 1 3 1 3 3 2 2 3 3 2 2 2 2 1 3 3 2
## [19981] 3 4 4 3 4 3 3 3 1 3 2 3 3 4 3 2 1 3 3 3 1 2 3 4 4 2 3 1 2 3 2 1 3 2 1 1
## [20017] 2 3 1 1 1 2 2 1 3 3 1 2 1 3 3 2 3 3 3 1 2 3 2 2 2 1 3 3 1 2 3 2 4 2 4 3
## [20053] 3 1 4 2 1 3 1 4 2 3 1 2 3 2 3 1 1 3 1 1 3 4 4 1 1 3 3 3 1 2 1 4 1 3 3 1
## [20089] 4 3 3 2 2 2 2 1 2 3 3 3 1 3 1 3 1 1 1 3 2 1 1 4 2 2 2 3 4 3 2 1 3 4 1 3
## [20125] 3 3 3 1 3 1 3 2 1 2 4 3 2 3 4 3 1 1 3 1 4 2 2 2 3 4 1 1 1 3 3 3 3 1 3 4
## [20161] 3 1 1 2 3 1 1 1 1 1 1 4 4 3 1 3 3 3 3 3 3 3 2 2 3 3 2 4 2 3 4 3 4 2 3 3
## [20197] 1 4 4 3 1 2 2 3 2 2 4 1 1 4 3 2 4 2 1 3 1 4 1 3 3 2 2 1 1 1 3 4 3 4 1 4
## [20233] 1 3 4 3 2 1 3 3 3 2 3 3 3 2 2 3 2 2 2 3 1 4 3 4 2 3 2 3 3 1 3 1 2 1 1 3
## [20269] 2 3 2 1 3 3 2 3 3 3 1 2 3 2 2 4 2 1 1 3 2 2 3 2 2 4 3 2 1 3 2 3 4 2 3 3
## [20305] 1 4 3 3 1 3 2 4 3 3 3 3 4 3 3 2 4 2 3 4 3 2 1 2 2 3 2 2 4 3 1 3 1 1 4 3
## [20341] 3 3 1 3 3 1 4 2 1 2 1 1 1 2 2 3 4 2 3 3 1 1 1 1 3 1 2 2 3 1 1 4 2 3 2 3
## [20377] 2 2 4 2 1 1 2 2 2 3 4 1 1 4 3 3 2 2 3 3 3 1 3 2 2 1 2 2 1 3 3 3 1 2 1 3
## [20413] 2 1 3 1 1 3 3 1 4 1 2 3 3 1 2 3 4 4 1 3 2 2 2 1 3 2 2 2 2 2 3 4 2 3 3 1
## [20449] 1 3 3 2 1 4 1 2 3 1 1 4 4 4 2 2 1 2 1 3 4 1 4 3 2 3 3 3 3 1 3 1 2 2 3 3
## [20485] 3 3 2 3 2 2 4 3 1 3 2 1 3 4 3 3 2 1 3 1 1 2 4 2 1 2 4 3 4 3 3 2 3 1 3 3
## [20521] 2 1 1 3 1 4 4 4 2 1 2 2 1 4 2 2 1 3 1 2 2 4 3 2 2 1 2 1 3 4 3 2 1 1 3 1
## [20557] 4 4 4 2 2 1 2 3 3 3 2 2 3 1 3 3 2 2 3 2 4 2 3 3 1 3 2 2 1 2 2 3 1 4 3 3
## [20593] 1 1 4 3 2 3 4 3 3 3 1 4 2 2 2 2 3 1 2 2 3 2 3 1 4 3 1 1 2 3 3 1 3 1 2 4
## [20629] 2 2 2 3 3 2 1 2 1 3 3 3 3 3 1 4 4 3 3 3 2 1 3 3 1 2 4 3 3 2 2 3 1 4 2 4
## [20665] 3 2 3 3 3 2 2 4 2 3 3 3 1 3 3 3 3 3 3 2 4 4 2 2 3 3 4 1 1 2 1 1 4 1 1 4
## [20701] 1 3 2 1 1 1 1 2 2 1 2 3 3 2 3 2 3 4 4 1 3 1 3 3 2 1 3 3 2 3 4 2 3 3 3 3
## [20737] 1 1 1 3 1 1 3 4 3 1 1 2 4 1 4 2 3 3 3 1 3 3 3 3 3 3 3 2 3 3 1 1 3 1 1 2
## [20773] 1 2 1 2 1 3 3 3 2 2 4 2 1 2 1 3 3 3 1 1 3 1 2 3 4 3 3 4 2 2 3 4 4 1 3 1
## [20809] 3 4 1 4 2 1 2 3 2 2 3 3 2 2 1 4 1 2 2 1 1 3 3 1 3 1 3 3 1 1 4 2 3 3 1 3
## [20845] 3 4 3 2 3 3 3 3 2 3 1 3 3 2 1 4 2 1 1 4 2 2 2 2 3 3 3 1 4 2 3 3 3 3 1 3
## [20881] 2 2 3 2 2 1 3 2 3 2 3 3 3 3 3 1 3 1 3 1 2 4 1 3 2 4 2 2 1 2 3 1 3 2 2 3
## [20917] 2 3 2 2 4 2 1 3 2 2 4 3 3 2 1 3 1 3 3 1 1 1 3 3 2 1 3 3 3 3 1 1 4 3 3 2
## [20953] 3 3 2 3 3 3 2 4 4 2 1 4 2 2 4 1 3 4 2 1 2 4 3 4 2 3 3 1 2 1 4 3 3 1 3 1
## [20989] 1 1 1 3 3 3 3 3 3 4 3 3 2 1 3 3 3 4 1 2 1 3 3 3 4 3 2 2 1 4 3 3 1 3 1 3
## [21025] 1 1 3 3 1 4 2 2 3 1 3 3 1 3 3 3 3 2 3 2 2 2 1 1 1 1 3 3 3 3 4 3 2 1 1 4
## [21061] 4 1 3 2 1 2 2 3 2 1 3 3 2 3 3 1 3 2 1 1 2 4 2 2 1 2 3 3 2 1 2 2 2 3 3 1
## [21097] 3 1 2 3 2 3 3 4 3 2 3 1 1 2 1 3 4 1 1 2 2 3 3 4 3 3 1 3 1 2 1 1 1 2 3 4
## [21133] 2 3 1 3 1 2 1 3 2 3 3 3 2 2 4 4 3 2 2 3 3 3 3 1 4 2 3 2 2 2 3 2 3 3 1 2
## [21169] 3 1 2 1 3 1 4 2 3 2 1 1 2 2 4 1 4 2 2 3 3 3 4 2 2 2 2 3 3 1 3 3 2 3 3 1
## [21205] 2 2 2 2 4 3 3 3 3 2 1 2 3 3 1 3 2 3 2 2 4 3 2 3 3 2 4 1 1 2 4 2 2 2 4 1
## [21241] 2 3 3 3 4 2 4 1 4 2 1 1 2 1 3 3 2 3 3 1 3 2 1 3 3 1 3 3 4 3 3 1 1 3 3 3
## [21277] 1 1 3 1 1 2 2 4 3 2 2 3 3 3 2 2 3 4 3 3 1 1 3 3 2 3 3 4 3 2 3 2 1 3 1 1
## [21313] 4 2 1 1 4 1 1 1 1 3 3 3 3 1 4 1 3 3 3 1 1 1 2 3 1 3 3 1 1 4 2 1 3 2 3 3
## [21349] 4 2 3 3 3 1 3 3 4 4 4 2 3 2 4 2 1 2 3 3 1 2 1 1 2 1 3 3 1 2 2 1 3 1 4 3
## [21385] 4 1 2 4 4 3 3 1 3 3 3 2 3 2 3 1 3 3 3 3 2 3 2 1 1 3 1 1 1 2 1 1 2 2 3 3
## [21421] 2 2 3 3 3 3 4 1 1 3 1 1 1 1 3 1 1 3 3 1 3 3 3 2 4 2 3 2 2 2 4 1 2 2 2 2
## [21457] 1 3 3 3 2 4 3 1 3 3 3 2 1 4 3 2 3 2 2 3 1 2 2 3 1 2 4 3 3 3 4 1 3 1 3 2
## [21493] 3 4 1 3 1 4 1 3 2 2 1 1 1 2 3 3 1 1 3 1 3 4 2 1 2 2 3 3 3 4 2 1 3 2 1 3
## [21529] 1 3 3 2 2 2 3 4 2 1 2 3 1 1 3 3 3 2 3 1 1 2 1 1 2 1 2 4 4 4 4 1 3 1 2 3
## [21565] 1 2 1 3 2 2 2 3 1 2 2 3 2 4 2 4 1 3 1 4 1 4 3 2 3 3 2 1 2 2 1 3 3 2 3 3
## [21601] 3 3 4 2 4 3 1 2 1 3 4 1 3 1 2 2 2 2 1 2 4 4 2 3 3 4 1 4 1 1 4 2 1 4 1 3
## [21637] 2 4 3 3 3 1 3 2 1 1 3 3 3 3 3 2 1 1 3 2 2 1 4 2 1 3 1 3 3 1 3 3 3 2 2 2
## [21673] 3 3 3 2 2 3 3 2 1 4 3 1 2 1 3 4 2 2 3 1 3 4 3 1 2 2 1 2 2 3 2 3 3 3 4 3
## [21709] 2 4 2 4 1 2 2 2 4 1 3 3 3 1 3 3 3 2 2 2 1 3 2 4 3 3 1 3 3 3 3 2 3 2 2 3
## [21745] 3 2 2 2 3 4 2 1 2 2 1 4 3 4 3 2 1 2 2 1 2 4 4 4 3 4 3 3 3 2 1 3 3 2 3 3
## [21781] 1 4 4 4 2 3 1 4 1 2 3 3 3 2 1 3 2 2 3 2 4 1 3 3 3 2 2 2 3 3 4 4 3 4 3 2
## [21817] 3 1 3 3 4 3 3 2 2 4 1 3 4 2 1 3 2 3 3 3 1 1 2 1 1 1 1 2 3 3 1 3 4 3 1 3
## [21853] 4 2 3 3 1 1 2 2 3 3 3 2 3 2 2 3 1 3 3 4 1 2 2 2 3 3 1 1 1 2 3 1 3 2 3 2
## [21889] 3 3 1 2 1 1 4 3 1 1 1 3 3 2 2 1 4 3 2 2 1 3 3 3 3 2 2 2 2 4 2 3 3 1 1 4
## [21925] 4 4 1 3 1 3 4 3 1 4 4 3 4 1 3 1 2 2 2 3 3 3 4 2 3 2 4 2 3 3 2 4 3 1 3 2
## [21961] 2 2 4 2 4 1 2 1 1 3 3 3 2 4 3 1 4 4 2 3 3 2 1 3 3 3 1 3 2 3 1 2 3 4 2 2
## [21997] 3 4 2 3 3 1 1 2 3 2 4 1 3 4 3 2 4 3 1 2 1 2 3 3 2 3 3 1 2 3 2 3 3 4 2 2
## [22033] 1 4 1 3 1 2 4 4 4 2 3 1 1 2 1 4 4 3 3 4 3 1 1 1 4 1 2 3 2 1 3 3 2 1 3 1
## [22069] 4 1 2 3 2 3 3 4 1 3 2 3 2 2 2 4 2 3 2 1 3 3 1 2 3 2 2 3 2 3 3 1 2 4 1 3
## [22105] 2 2 2 1 1 2 3 1 3 1 2 2 3 3 4 2 3 3 3 4 3 3 3 4 3 1 2 3 4 1 2 3 3 2 2 2
## [22141] 2 3 2 3 4 4 1 2 1 1 2 3 2 3 4 2 2 4 3 4 3 3 4 2 1 3 1 3 4 1 1 3 3 3 3 3
## [22177] 3 2 1 3 3 3 1 2 3 3 2 2 1 3 3 2 3 2 3 4 3 4 2 1 2 3 1 4 2 3 2 3 3 3 3 4
## [22213] 4 2 4 3 2 3 2 4 1 4 2 4 2 1 1 2 1 2 1 2 4 1 2 1 1 2 3 3 2 1 2 3 2 3 2 4
## [22249] 2 4 2 2 4 3 2 1 1 4 1 2 3 2 1 4 3 2 2 3 3 2 3 2 4 3 3 2 4 3 2 4 3 4 3 1
## [22285] 1 3 1 3 1 2 4 2 4 3 2 3 4 3 2 4 1 2 1 1 3 2 3 4 4 2 2 3 3 2 3 1 1 2 4 3
## [22321] 4 2 1 2 1 2 3 3 3 2 4 1 4 3 1 3 1 1 3 3 2 4 3 3 3 2 3 3 4 2 3 1 1 1 4 4
## [22357] 2 3 2 3 3 2 3 2 3 3 4 1 2 3 3 3 3 3 1 3 4 3 2 2 3 3 1 3 2 2 2 3 2 4 4 4
## [22393] 3 2 4 2 2 2 1 3 3 3 2 3 1 1 3 1 1 1 1 4 2 2 3 3 2 1 4 1 4 2 3 1 4 3 3 1
## [22429] 3 1 2 1 3 4 1 1 3 3 1 3 4 4 4 1 1 1 1 4 2 4 3 2 3 2 3 2 1 2 3 3 2 1 4 3
## [22465] 2 2 3 2 3 3 2 3 2 2 3 1 3 2 2 1 1 4 2 1 4 3 3 4 4 2 3 3 1 3 1 2 3 4 3 3
## [22501] 3 3 3 2 3 1 3 1 3 2 1 3 4 2 3 3 3 1 1 4 1 1 4 1 4 3 2 3 3 2 2 3 3 3 1 1
## [22537] 3 1 3 2 3 3 1 1 2 4 4 2 3 2 2 3 3 1 1 2 4 1 4 2 4 1 3 3 3 3 2 3 1 1 3 4
## [22573] 1 1 3 3 3 2 2 1 3 2 4 4 2 2 2 3 3 3 4 3 2 3 3 2 1 3 1 2 3 3 1 1 3 1 2 1
## [22609] 1 3 3 2 1 1 2 1 2 3 3 2 3 1 3 3 2 2 1 2 1 2 3 3 2 2 3 1 2 4 1 2 1 3 3 3
## [22645] 1 1 3 1 3 3 3 4 3 3 3 3 1 1 3 3 1 4 3 1 1 1 1 2 3 2 2 1 2 1 2 2 3 3 4 1
## [22681] 4 1 3 3 1 3 2 4 3 2 3 1 4 2 3 3 3 4 1 3 4 1 3 1 2 1 4 2 3 1 3 2 4 2 2 3
## [22717] 4 3 3 1 2 1 2 3 3 3 1 1 2 3 2 2 3 4 2 4 1 3 3 3 2 1 4 3 2 2 1 3 3 1 3 2
## [22753] 2 3 4 2 4 2 3 2 1 1 4 3 3 2 3 2 1 1 1 3 2 4 3 2 1 4 1 2 2 4 2 3 3 4 1 3
## [22789] 3 1 3 2 4 3 1 3 3 3 2 2 3 2 2 2 1 4 2 1 4 1 1 3 1 3 2 2 1 3 3 3 3 1 1 1
## [22825] 3 2 2 3 3 1 3 4 2 4 3 2 2 3 1 3 3 1 1 3 4 1 1 2 3 3 3 3 1 4 3 1 1 3 1 4
## [22861] 2 3 3 1 1 3 2 2 2 4 3 3 3 3 1 3 4 1 3 1 4 1 2 4 3 4 4 3 3 2 1 2 3 3 2 1
## [22897] 3 4 3 3 3 3 4 2 3 1 1 4 3 1 4 2 4 2 3 3 1 2 2 2 2 4 3 2 1 1 3 1 2 1 1 2
## [22933] 1 3 3 4 3 3 1 2 1 1 3 3 4 2 2 3 1 3 4 3 1 3 1 3 3 3 1 4 3 2 1 1 1 3 1 2
## [22969] 2 3 2 4 3 4 3 2 3 2 3 1 3 3 3 3 3 2 4 3 3 2 4 2 1 3 1 1 4 1 1 2 1 1 4 3
## [23005] 2 3 3 3 1 3 2 2 3 1 1 3 3 3 1 2 3 3 2 1 2 2 1 2 1 3 3 3 3 3 3 3 3 3 1 2
## [23041] 4 1 3 3 1 3 3 4 3 4 2 1 3 3 4 3 2 2 4 3 2 2 4 3 2 1 1 2 3 2 1 1 2 3 2 4
## [23077] 3 3 3 4 3 1 1 1 1 2 1 2 3 2 2 3 1 1 1 3 3 2 2 1 2 3 1 2 2 3 4 1 1 2 2 1
## [23113] 4 1 2 3 1 3 3 2 2 3 3 3 4 1 1 3 4 2 3 1 1 3 2 3 4 2 1 3 2 1 4 4 2 4 2 3
## [23149] 3 3 1 2 1 1 2 4 2 1 2 1 2 2 3 3 3 3 3 3 3 1 2 3 4 1 3 3 2 4 2 1 3 3 1 4
## [23185] 3 2 3 2 3 3 2 1 3 3 1 3 3 3 3 3 4 3 3 3 2 2 2 2 2 4 2 2 1 3 3 1 2 3 4 4
## [23221] 3 3 4 1 2 4 2 3 3 1 1 2 3 4 3 1 3 3 4 2 3 4 2 4 3 1 3 3 2 2 1 2 2 3 3 3
## [23257] 2 2 3 1 2 3 1 3 3 3 3 4 2 3 1 4 1 3 3 2 3 2 3 3 4 2 2 2 1 2 2 1 3 3 3 3
## [23293] 2 3 1 2 1 1 2 3 2 1 3 3 2 2 1 1 1 3 2 1 3 4 3 2 4 2 4 3 2 3 3 1 2 1 3 4
## [23329] 4 2 1 1 3 1 3 2 1 1 1 3 4 3 3 2 3 1 4 4 2 3 2 2 1 4 4 3 1 3 3 1 1 2 2 3
## [23365] 1 2 2 3 2 3 1 1 1 3 1 2 1 3 2 2 3 4 4 1 1 3 3 2 1 3 4 2 2 2 4 3 3 2 2 2
## [23401] 3 4 1 3 2 1 3 2 4 2 3 2 2 3 1 1 2 1 2 4 2 3 1 1 1 3 3 3 4 4 3 3 2 1 2 3
## [23437] 3 2 3 1 3 1 3 1 1 1 2 3 3 3 2 1 3 4 3 3 1 2 3 2 2 2 1 2 2 2 1 3 3 1 3 1
## [23473] 4 4 1 2 2 3 2 4 2 1 1 1 3 3 3 4 1 4 1 1 1 3 3 3 1 1 3 1 3 2 1 1 1 1 2 4
## [23509] 4 1 4 3 2 3 1 1 2 4 2 3 2 2 2 4 2 3 2 4 2 4 2 3 4 2 3 3 2 3 3 3 4 4 1 4
## [23545] 3 2 3 2 3 4 3 2 2 3 1 1 3 2 2 3 3 1 4 3 3 3 1 1 2 2 3 2 3 3 3 3 1 3 4 3
## [23581] 2 1 4 2 2 1 3 1 3 1 3 1 2 2 1 3 2 1 3 3 4 1 3 3 4 3 2 1 1 3 3 3 3 3 2 2
## [23617] 4 3 4 2 1 3 1 4 2 1 3 3 3 2 1 3 1 4 3 3 1 3 2 3 2 2 1 4 4 2 3 2 2 2 2 2
## [23653] 2 3 1 2 1 1 3 2 3 3 3 2 2 1 3 1 3 3 3 3 1 3 3 4 3 3 2 3 3 3 3 3 1 2 2 1
## [23689] 1 3 3 2 1 4 3 2 4 1 3 3 2 3 3 3 1 2 1 1 3 4 3 2 3 3 2 3 4 3 1 3 2 3 4 1
## [23725] 3 4 4 1 1 1 1 3 3 3 3 3 2 3 1 4 4 3 2 2 1 4 2 3 3 1 1 1 1 1 3 2 2 4 2 4
## [23761] 3 3 2 1 1 4 1 2 2 1 1 4 1 2 3 1 3 3 1 3 1 3 3 3 1 2 2 1 1 2 1 1 1 4 2 3
## [23797] 1 2 3 3 1 3 3 3 4 1 1 3 2 2 3 3 2 3 4 3 4 2 3 3 3 1 3 3 4 3 3 4 4 1 2 3
## [23833] 3 3 1 1 1 3 4 3 1 1 1 4 3 2 4 2 3 2 1 2 4 4 2 3 1 4 3 3 1 3 3 3 2 3 4 1
## [23869] 1 2 2 4 2 2 2 1 2 2 3 3 3 2 4 2 2 3 4 4 3 3 1 4 3 3 3 2 4 3 4 3 1 1 2 3
## [23905] 3 3 2 2 1 3 3 4 1 3 1 4 3 2 2 1 3 2 1 3 3 4 3 2 1 2 4 3 3 3 1 3 3 1 3 1
## [23941] 3 3 2 4 4 4 2 4 1 1 2 4 3 2 1 4 3 4 3 2 2 3 3 1 3 3 3 1 1 1 2 1 3 2 1 2
## [23977] 3 1 3 1 1 2 3 2 3 1 1 2 3 2 3 2 3 2 3 2 4 4 2 3 4 3 1 3 3 4 4 2 3 3 4 4
## [24013] 3 3 4 2 3 2 3 2 3 3 2 3 2 3 3 1 3 3 1 2 3 3 3 1 2 3 1 1 3 2 2 2 1 4 2 2
## [24049] 3 2 2 3 2 3 1 1 3 2 3 3 4 2 2 1 3 3 3 3 4 2 1 1 2 1 1 2 4 3 1 3 1 3 2 3
## [24085] 3 1 1 3 3 2 3 1 3 3 2 2 2 3 2 2 2 3 1 1 2 3 2 1 4 3 2 1 2 3 3 2 4 3 3 3
## [24121] 1 3 3 3 1 1 2 1 1 2 3 3 4 3 3 1 2 1 3 3 3 2 2 2 4 2 2 3 2 1 1 1 4 3 3 3
## [24157] 1 1 4 4 2 3 3 3 3 1 1 3 4 2 1 3 2 3 2 4 1 2 4 1 2 1 3 1 1 2 2 3 2 2 3 1
## [24193] 2 3 2 1 3 1 4 3 3 3 3 2 2 1 2 2 1 1 3 2 3 2 2 2 3 1 3 1 2 1 3 3 3 4 4 2
## [24229] 2 4 1 3 1 1 3 2 2 3 4 3 4 2 3 3 2 3 4 3 1 1 1 3 3 2 3 1 2 3 3 1 2 2 3 3
## [24265] 1 2 3 2 2 1 1 2 1 1 3 1 2 2 1 4 1 2 3 3 3 1 3 1 1 1 1 2 2 3 3 3 2 3 3 1
## [24301] 2 3 3 2 2 2 1 3 4 2 2 2 3 1 3 4 2 4 1 1 4 3 2 1 3 3 1 1 2 1 3 1 1 3 2 2
## [24337] 2 3 1 3 2 3 3 3 2 1 4 3 3 4 1 4 2 2 3 2 3 2 1 2 3 3 3 4 4 3 3 3 2 2 1 3
## [24373] 4 2 1 3 3 4 1 2 2 3 2 1 3 3 2 1 1 2 3 3 1 3 3 1 4 3 1 1 3 3 1 2 3 1 3 2
## [24409] 3 2 3 2 1 2 3 1 2 2 1 2 3 3 2 3 3 3 3 3 2 4 1 3 3 1 1 2 2 2 3 3 2 2 3 3
## [24445] 3 3 2 1 2 2 2 2 2 1 1 3 3 2 4 2 1 1 3 2 3 2 3 3 3 2 2 3 2 1 2 3 1 1 3 2
## [24481] 3 1 2 3 1 1 3 3 4 1 4 3 1 2 3 4 2 2 1 4 2 3 4 3 3 1 3 2 2 4 4 2 2 3 3 3
## [24517] 3 2 4 3 1 2 2 3 4 3 1 3 3 1 1 3 2 1 1 1 3 4 1 4 3 2 4 2 3 1 4 3 1 3 3 3
## [24553] 3 3 1 3 4 2 4 3 3 4 2 4 3 4 3 1 3 3 2 2 3 4 2 3 3 2 2 3 3 1 2 1 4 4 3 4
## [24589] 4 3 3 1 3 3 3 2 3 3 3 2 2 3 3 3 3 1 2 3 2 1 2 2 4 3 1 2 2 3 1 3 1 1 3 4
## [24625] 2 3 2 3 2 2 4 4 2 3 2 2 3 1 1 3 2 1 4 2 1 4 2 3 3 3 1 1 2 3 3 3 1 3 3 2
## [24661] 3 4 2 2 1 3 4 3 2 1 3 3 2 1 1 4 4 4 3 2 1 1 3 2 4 3 2 3 2 2 1 2 1 2 3 3
## [24697] 2 4 1 1 1 1 1 3 3 1 4 2 2 4 3 1 3 3 2 4 2 2 3 2 1 2 3 2 2 1 1 2 3 4 2 2
## [24733] 1 3 2 4 3 3 1 3 4 2 3 2 3 1 3 1 3 1 1 3 1 1 1 4 3 1 3 3 2 2 2 3 2 2 3 1
## [24769] 3 1 2 1 1 1 3 1 2 3 2 3 3 4 1 3 2 1 1 2 3 1 3 4 1 3 2 1 3 4 3 1 3 2 3 2
## [24805] 3 4 1 1 3 3 3 4 1 3 3 4 1 4 2 2 4 2 2 4 2 3 3 3 3 4 4 1 1 2 3 1 1 2 2 2
## [24841] 3 2 3 3 2 3 2 1 3 2 2 3 1 1 3 4 3 3 3 2 3 2 2 3 3 2 3 4 1 3 3 1 1 3 3 2
## [24877] 3 4 2 3 2 3 2 2 1 1 3 4 3 4 2 3 3 3 2 2 2 3 3 2 4 4 2 2 3 3 3 3 3 4 3 2
## [24913] 2 2 2 4 1 4 3 3 3 2 3 4 2 2 3 3 2 3 2 2 2 1 3 3 3 3 1 2 3 1 4 1 3 3 3 1
## [24949] 3 3 1 2 2 2 3 3 4 2 1 1 1 3 2 2 1 3 4 2 2 1 3 2 2 4 3 3 3 3 1 3 2 2 1 2
## [24985] 3 3 4 1 3 2 1 2 4 3 4 2 3 4 2 3 3 4 2 2 2 3 4 2 1 1 1 4 3 2 2 3 3 1 4 3
## [25021] 2 3 1 1 2 1 2 3 1 2 3 1 3 3 3 4 3 3 3 1 3 3 3 3 1 3 3 3 3 2 2 1 3 3 3 1
## [25057] 1 4 2 2 3 1 4 2 2 2 2 3 1 3 2 1 2 1 4 3 2 4 1 2 3 2 1 3 2 2 4 2 1 3 2 1
## [25093] 2 2 3 3 1 3 1 1 1 2 1 2 3 2 1 2 1 2 3 1 4 3 1 2 3 3 3 2 1 1 3 3 4 3 1 2
## [25129] 3 3 3 2 3 1 3 1 4 3 1 4 3 3 1 3 4 4 3 3 2 3 1 1 4 1 1 2 3 2 3 3 1 4 3 1
## [25165] 4 2 3 1 2 4 4 2 3 4 4 4 4 4 2 3 1 4 3 2 4 2 2 2 1 2 3 2 2 4 1 3 3 2 2 4
## [25201] 2 2 1 4 3 3 3 3 1 4 3 2 1 3 1 1 2 2 2 3 2 1 3 1 2 2 1 3 2 3 2 2 3 2 2 3
## [25237] 1 2 2 3 3 2 2 4 1 1 1 2 2 3 3 1 3 1 2 1 1 3 3 1 3 3 3 1 3 4 1 1 4 2 3 1
## [25273] 1 1 1 2 2 3 3 3 2 2 2 2 3 3 2 2 3 4 1 3 3 3 4 3 3 4 3 3 4 1 3 2 1 4 2 2
## [25309] 1 2 3 3 3 1 1 1 3 3 3 2 4 1 4 3 1 3 1 1 4 3 2 3 2 2 3 1 2 3 2 3 2 1 4 4
## [25345] 3 3 1 3 2 2 2 3 1 3 3 2 4 1 1 2 3 3 1 2 3 2 1 4 4 3 1 4 2 3 2 2 2 2 3 1
## [25381] 4 4 2 1 1 4 4 3 2 2 1 4 3 4 3 2 3 1 3 3 3 2 4 1 2 2 2 3 3 2 2 3 3 1 2 1
## [25417] 3 4 4 1 1 3 2 2 1 3 2 2 2 3 4 3 2 3 3 2 2 3 4 2 2 1 1 3 1 2 3 2 3 3 3 3
## [25453] 3 3 4 3 1 1 3 4 3 3 4 3 1 2 1 2 2 3 3 2 2 1 3 1 1 4 4 4 1 3 2 3 2 2 3 1
## [25489] 2 2 1 4 1 3 1 3 1 2 3 4 3 3 3 3 3 1 3 2 3 3 2 4 1 3 1 1 3 3 3 4 2 2 1 1
## [25525] 3 3 3 2 3 4 2 1 2 1 1 3 3 1 2 1 3 2 1 3 4 4 1 3 2 3 3 4 3 3 1 1 1 4 3 1
## [25561] 3 4 2 2 3 3 2 3 1 2 1 2 3 2 2 2 3 3 3 3 4 1 2 3 2 3 4 1 2 3 4 3 3 2 4 4
## [25597] 3 3 1 2 3 3 1 3 2 3 3 3 2 3 1 1 2 2 1 2 3 3 2 1 3 1 3 3 2 4 3 4 1 2 3 3
## [25633] 2 2 3 2 3 3 3 2 2 1 2 3 2 4 1 1 2 3 2 4 3 3 3 1 4 3 3 3 3 3 4 3 1 4 1 3
## [25669] 2 3 3 3 3 4 2 2 3 2 1 2 4 3 1 2 2 1 3 3 3 4 3 2 1 3 3 3 3 2 3 2 3 3 3 3
## [25705] 4 3 2 3 3 4 3 1 4 3 2 2 1 2 3 3 4 4 3 2 3 3 1 1 3 2 2 3 2 4 3 2 2 2 2 3
## [25741] 1 4 3 2 3 1 2 1 4 1 1 3 3 3 3 3 2 1 4 1 4 3 4 3 1 4 2 1 2 4 1 1 4 2 2 3
## [25777] 2 2 3 2 1 1 1 1 2 2 2 2 3 2 4 3 1 1 2 2 4 3 2 1 1 2 2 1 3 4 4 3 2 1 1 3
## [25813] 4 2 1 2 4 3 1 3 1 3 4 1 3 4 3 1 3 1 2 4 3 2 3 1 3 3 3 1 3 3 3 1 2 4 4 1
## [25849] 4 2 2 3 1 1 1 3 1 1 3 1 1 4 1 3 2 2 3 1 2 1 3 2 3 4 1 1 1 3 4 3 1 1 3 1
## [25885] 1 4 3 3 3 3 3 3 2 4 1 3 2 3 3 2 1 2 4 2 4 2 1 1 3 4 1 1 1 4 3 3 4 1 2 2
## [25921] 1 2 3 4 3 2 3 4 4 2 1 3 3 2 2 1 3 3 3 3 2 3 3 1 3 4 4 3 3 3 1 4 1 2 3 3
## [25957] 3 3 4 1 3 4 4 1 1 4 2 1 2 2 3 4 4 2 2 3 3 3 3 4 3 3 3 3 3 2 2 2 4 3 2 1
## [25993] 2 1 3 3 2 2 2 1 3 3 1 1 3 1 2 3 4 2 1 1 3 3 2 3 1 2 1 2 3 3 1 3 3 1 3 2
## [26029] 1 2 4 3 3 2 3 2 1 4 3 4 4 3 3 3 3 1 3 4 1 3 1 3 3 3 3 3 1 2 4 3 1 4 3 2
## [26065] 1 4 2 4 3 1 2 3 3 3 2 4 2 3 1 3 4 3 3 4 3 2 3 1 2 3 1 2 2 3 3 2 3 3 2 1
## [26101] 3 1 4 1 1 1 3 3 2 2 3 3 3 2 2 4 3 2 1 2 3 4 1 3 4 3 1 1 1 3 4 3 1 4 3 1
## [26137] 2 1 2 1 3 2 4 3 2 4 1 2 1 2 2 3 2 2 2 2 2 3 3 1 2 1 2 3 1 1 1 3 4 2 1 2
## [26173] 3 2 3 3 3 3 1 4 2 3 1 3 2 3 2 2 2 1 2 3 1 2 1 3 3 3 1 2 3 2 3 2 1 1 3 2
## [26209] 1 3 4 1 1 2 3 1 3 2 4 3 3 4 2 3 3 4 2 3 1 1 3 1 3 3 3 1 3 4 1 1 1 3 3 2
## [26245] 2 3 4 2 3 1 1 3 3 4 1 2 3 3 2 3 3 2 4 2 2 4 3 2 1 3 1 2 3 3 2 1 2 2 3 4
## [26281] 2 1 3 1 3 4 1 3 3 1 2 1 1 1 2 3 1 1 3 1 1 1 2 4 3 1 3 2 2 1 4 4 1 2 3 2
## [26317] 2 4 3 2 2 1 3 4 1 3 1 3 2 2 4 3 3 2 3 3 2 3 2 1 2 1 2 2 3 3 3 4 3 1 2 3
## [26353] 3 4 1 2 3 3 1 1 3 1 2 3 2 1 3 3 1 1 3 3 3 2 4 2 4 2 1 4 1 4 2 2 1 2 1 2
## [26389] 3 3 2 3 1 3 3 3 2 1 2 1 2 3 1 2 1 2 3 2 2 3 3 2 3 2 4 4 1 4 3 2 4 3 3 1
## [26425] 3 2 1 3 3 1 1 3 3 3 3 4 3 2 2 2 3 4 3 2 3 1 2 2 1 1 4 3 2 1 3 3 3 2 1 1
## [26461] 3 3 3 2 1 4 1 4 3 3 3 3 2 3 3 2 1 3 3 3 2 4 2 1 3 3 3 4 2 3 3 3 3 4 1 1
## [26497] 1 4 3 4 1 1 2 4 2 1 3 2 3 1 3 3 4 2 2 2 2 3 2 1 1 1 3 1 2 1 3 3 3 1 3 2
## [26533] 3 2 2 3 2 1 3 1 3 3 1 1 3 3 3 2 2 3 1 1 1 2 4 4 2 1 1 1 2 1 2 2 1 4 3 3
## [26569] 1 1 1 3 3 3 3 3 2 2 1 4 1 1 3 3 2 2 1 2 2 2 2 3 3 3 1 3 2 1 1 1 1 4 1 1
## [26605] 2 3 2 3 3 1 2 3 3 1 2 3 3 1 1 3 4 2 1 2 4 2 2 2 1 3 3 1 2 2 2 3 2 3 2 3
## [26641] 1 3 2 3 4 4 2 2 1 2 4 1 2 2 3 4 4 4 3 1 3 4 3 2 2 3 4 3 4 4 2 2 2 2 3 3
## [26677] 3 4 3 1 2 4 2 4 3 4 2 2 3 3 1 2 3 3 2 3 3 4 3 2 3 3 2 1 3 2 3 4 3 3 2 4
## [26713] 3 3 3 2 3 2 2 3 1 4 3 2 2 1 3 3 3 2 2 2 4 4 2 1 2 3 3 3 1 2 3 3 1 3 2 3
## [26749] 4 1 3 4 4 3 3 4 3 4 3 4 3 4 3 1 4 3 1 3 2 1 3 2 3 4 2 1 2 3 2 1 1 1 2 2
## [26785] 1 3 3 1 3 3 3 3 1 3 2 4 3 4 3 4 4 4 2 1 3 3 1 3 1 2 4 2 2 3 1 3 2 2 2 4
## [26821] 2 1 2 2 2 2 4 3 4 4 2 2 2 2 2 1 1 2 3 2 3 1 1 4 4 2 1 1 3 3 4 2 1 2 1 1
## [26857] 2 1 3 4 3 2 2 1 3 3 1 2 2 1 2 1 4 3 3 3 2 2 2 3 2 2 2 1 4 1 3 3 2 4 1 3
## [26893] 1 3 3 3 2 1 4 4 2 1 4 3 3 2 3 3 3 4 3 1 4 4 1 1 4 1 3 2 2 2 4 3 1 4 3 3
## [26929] 1 1 3 1 3 3 4 3 3 1 3 2 3 1 3 3 1 2 1 3 1 1 1 4 1 4 1 4 3 4 3 3 3 1 1 4
## [26965] 3 3 2 3 3 2 2 3 3 1 4 1 3 1 2 3 3 1 3 1 1 4 1 4 1 3 2 3 2 2 4 4 2 3 3 2
## [27001] 2 4 2 3 3 4 1 2 3 3 1 1 3 2 2 4 4 3 3 1 3 1 3 2 1 2 1 2 3 2 3 1 1 2 4 2
## [27037] 1 1 1 1 4 1 4 3 3 2 2 3 1 1 3 3 3 3 2 3 2 4 3 2 4 2 3 3 2 3 3 3 3 2 1 4
## [27073] 3 3 1 1 3 1 3 2 3 3 3 2 3 3 2 3 3 1 1 3 2 3 2 3 3 4 3 1 4 3 3 1 1 3 1 4
## [27109] 1 1 1 3 3 2 1 3 2 2 4 1 3 2 1 1 1 2 1 3 3 2 3 2 2 2 2 1 3 1 3 1 2 2 1 3
## [27145] 1 3 3 2 3 3 2 3 4 2 2 2 3 2 4 1 3 3 1 3 3 3 1 4 1 1 2 2 1 3 3 1 1 1 2 3
## [27181] 1 3 1 1 2 3 1 3 4 3 1 2 3 3 4 1 4 1 1 3 1 1 1 3 3 3 3 4 3 2 2 3 1 2 3 3
## [27217] 1 1 1 3 1 3 1 3 4 3 3 1 1 1 4 3 4 2 3 1 4 2 2 3 2 3 3 2 3 2 3 2 2 1 1 1
## [27253] 3 1 1 2 2 1 2 3 1 1 3 3 3 2 3 2 2 3 3 3 1 1 1 1 2 3 1 4 2 2 2 2 3 2 3 1
## [27289] 3 3 4 4 2 1 1 2 3 3 4 2 4 3 1 4 2 3 1 2 3 3 3 3 3 3 3 2 2 4 1 1 1 3 3 3
## [27325] 3 3 2 4 3 3 2 3 1 1 3 3 1 4 3 1 2 3 2 3 2 3 1 1 3 3 1 3 2 3 4 2 1 4 1 4
## [27361] 3 4 4 3 3 3 3 4 1 3 2 3 1 2 3 3 2 4 2 3 3 1 3 2 3 4 3 3 3 3 4 2 1 3 4 2
## [27397] 3 3 3 3 3 3 3 2 3 2 2 2 4 2 4 3 3 3 2 2 4 3 2 4 1 4 2 4 4 2 4 3 3 2 1 2
## [27433] 3 2 3 3 4 1 1 2 3 2 1 3 1 4 2 4 3 3 2 3 1 4 4 3 1 2 3 3 2 1 3 3 4 2 1 1
## [27469] 4 1 2 3 2 4 4 2 1 3 2 1 4 2 2 1 2 2 1 1 4 2 1 3 1 4 1 3 3 1 3 1 2 3 2 2
## [27505] 1 1 3 3 1 1 3 2 1 2 2 3 1 1 2 1 1 3 3 3 4 3 3 3 3 1 1 1 2 3 2 1 1 3 3 3
## [27541] 2 4 2 1 3 3 3 4 4 2 2 1 2 3 3 4 2 2 2 4 1 1 2 4 3 1 1 3 1 3 2 3 3 2 3 3
## [27577] 4 1 3 3 4 3 1 1 4 3 3 3 3 3 3 2 2 1 3 3 3 3 1 1 2 2 2 3 4 1 4 1 1 2 3 2
## [27613] 1 4 3 3 3 3 1 2 2 3 1 3 3 4 3 3 1 1 2 1 2 3 1 2 3 1 1 2 1 2 2 1 1 2 2 1
## [27649] 3 2 3 2 3 4 1 2 1 2 1 3 2 2 2 2 2 1 4 2 1 3 1 3 2 2 3 1 1 2 3 2 3 1 3 3
## [27685] 3 1 3 3 4 3 2 1 2 2 3 2 2 1 3 4 2 1 3 1 1 1 3 3 3 1 1 4 2 3 2 2 3 3 2 4
## [27721] 3 3 1 1 1 2 1 3 3 1 3 3 3 3 1 2 1 3 2 4 3 4 3 3 1 1 3 3 2 4 2 2 3 2 3 2
## [27757] 1 2 3 3 2 4 2 3 3 1 2 2 1 3 1 2 3 4 3 2 1 3 2 1 4 3 2 3 3 4 4 2 2 3 1 4
## [27793] 4 1 3 2 3 1 2 2 2 2 4 3 3 1 1 2 1 3 1 3 3 3 2 3 2 3 4 3 3 3 3 3 2 2 1 1
## [27829] 1 4 3 4 1 1 1 2 4 2 3 3 2 3 2 3 3 3 2 3 3 3 1 2 3 1 1 1 3 2 3 3 2 4 4 2
## [27865] 1 3 3 2 3 2 3 2 4 2 1 2 3 1 3 1 2 3 4 3 1 3 4 3 1 4 1 3 3 1 3 3 3 4 3 2
## [27901] 3 3 3 2 2 1 1 2 1 3 3 2 3 2 2 1 1 1 1 3 2 1 1 3 1 3 3 3 3 3 3 2 1 1 4 4
## [27937] 2 1 1 3 2 3 3 2 3 2 3 3 3 1 1 4 3 1 2 3 2 2 2 3 3 1 4 1 3 2 4 4 3 3 1 3
## [27973] 1 2 1 1 1 1 2 3 3 1 2 4 1 1 3 1 3 1 1 1 1 3 2 2 2 2 3 1 3 3 1 4 1 3 1 3
## [28009] 1 2 2 4 1 4 3 2 3 1 2 1 3 3 1 4 1 3 2 3 2 3 2 2 3 2 1 3 4 3 2 1 2 4 2 1
## [28045] 3 3 1 2 2 3 3 4 3 3 3 2 1 3 2 3 3 3 4 1 1 2 1 3 3 1 3 4 1 3 1 2 1 3 3 3
## [28081] 3 3 2 3 3 1 1 3 2 3 3 3 2 2 3 2 3 1 3 1 3 4 1 2 3 3 2 4 3 1 3 1 2 2 1 1
## [28117] 1 2 4 1 1 2 2 2 2 1 3 2 2 3 2 2 3 2 1 2 4 4 1 2 3 1 4 3 3 1 4 1 1 3 2 4
## [28153] 3 2 2 3 3 3 2 3 1 3 1 4 4 1 2 4 3 3 3 2 4 3 3 4 4 2 3 1 3 1 1 1 3 1 1 4
## [28189] 2 2 2 1 3 1 2 4 3 4 1 3 2 2 2 3 3 4 2 3 2 1 3 3 3 3 4 1 3 4 3 3 4 2 1 2
## [28225] 2 3 3 2 3 3 3 3 2 2 3 2 3 1 2 3 2 4 3 2 4 2 1 1 4 1 1 1 1 1 3 2 2 2 1 2
## [28261] 3 1 1 3 1 3 2 1 1 2 1 3 2 2 1 1 1 1 1 4 2 4 2 1 2 2 1 4 3 3 2 1 4 1 2 3
## [28297] 4 2 1 2 2 3 2 3 2 2 1 1 1 3 3 3 3 1 2 3 2 4 3 2 1 2 3 1 4 2 2 1 4 2 3 2
## [28333] 2 1 2 2 2 3 4 3 2 1 4 2 4 1 1 2 3 3 3 2 3 3 3 2 1 3 4 1 2 4 1 3 4 3 4 1
## [28369] 2 2 3 2 3 4 2 2 1 1 4 3 2 4 3 3 1 2 3 2 2 3 3 4 1 2 2 3 4 1 2 2 1 4 3 1
## [28405] 1 1 4 2 1 1 3 3 1 3 2 4 4 4 3 1 3 3 2 3 3 3 2 1 1 1 1 3 2 1 2 1 3 2 3 4
## [28441] 3 1 3 3 3 1 3 3 1 2 3 3 3 2 2 2 2 1 3 2 3 1 3 3 4 1 3 2 1 3 3 4 2 3 4 3
## [28477] 4 3 2 1 1 3 2 4 2 4 3 1 3 1 4 3 2 3 1 4 1 3 1 4 1 4 2 2 4 3 1 1 3 2 1 3
## [28513] 1 2 1 2 1 3 2 3 3 3 3 1 2 4 3 3 4 3 2 3 1 2 4 4 1 1 1 3 1 1 4 4 1 1 3 1
## [28549] 1 3 3 4 2 3 1 1 1 3 2 3 1 2 1 4 1 1 1 2 1 1 2 1 3 2 3 1 1 1 2 2 3 4 4 2
## [28585] 4 2 1 1 2 4 3 3 3 1 3 3 1 3 3 4 3 4 3 3 3 3 3 2 2 1 1 2 4 2 2 3 4 3 2 3
## [28621] 3 2 1 3 1 3 1 1 3 2 1 3 1 3 1 2 1 1 3 3 3 3 3 3 2 3 3 4 1 2 2 3 1 4 2 3
## [28657] 3 1 3 2 3 1 4 4 3 2 1 3 2 3 1 2 1 1 1 3 2 3 2 4 2 2 2 1 3 2 3 3 1 2 3 3
## [28693] 3 4 3 2 3 3 3 3 3 1 1 2 2 3 3 4 3 3 2 2 2 1 3 3 1 4 3 2 3 2 1 4 3 3 2 1
## [28729] 1 2 2 1 2 4 2 2 2 3 1 1 1 3 4 2 1 3 2 3 4 2 3 1 3 3 4 3 3 1 1 3 3 3 2 4
## [28765] 2 2 1 2 2 3 3 3 3 4 2 3 3 3 4 1 2 3 3 2 2 2 1 2 4 2 2 3 3 3 3 4 1 3 1 3
## [28801] 1 3 1 2 2 1 3 3 2 4 3 3 4 1 3 3 3 3 1 2 3 2 4 1 2 2 3 1 1 2 1 1 2 4 4 2
## [28837] 1 1 3 3 3 2 3 2 2 4 3 2 2 3 3 1 4 4 4 2 2 3 1 4 1 4 1 3 3 1 3 3 2 1 4 3
## [28873] 3 3 1 3 4 2 3 1 1 3 3 2 3 3 4 2 1 3 3 1 3 1 2 3 1 3 4 3 3 4 3 2 3 3 1 2
## [28909] 3 3 2 3 3 2 3 2 4 3 2 2 3 4 3 2 3 2 1 1 3 3 1 3 3 4 2 4 3 2 1 4 2 4 1 3
## [28945] 1 1 1 1 1 2 3 1 3 3 2 3 3 3 1 1 3 3 3 2 2 1 1 3 1 1 2 2 3 3 3 1 3 3 1 1
## [28981] 2 2 2 2 2 2 3 2 2 1 3 3 4 3 4 4 4 1 3 3 3 3 3 4 3 1 2 1 3 4 2 4 1 3 1 1
## [29017] 3 2 2 4 2 2 3 1 1 2 1 3 2 1 4 4 1 3 2 1 1 1 4 2 4 2 1 3 4 2 2 3 1 4 1 3
## [29053] 3 2 3 3 3 3 1 1 4 2 1 1 2 3 3 3 3 2 4 2 3 2 1 2 3 1 3 4 3 3 3 3 1 1 4 1
## [29089] 1 3 1 1 2 4 2 1 2 2 3 1 1 4 2 3 2 1 1 2 3 3 1 1 3 2 3 4 1 1 3 2 3 2 4 3
## [29125] 3 4 4 3 2 3 1 1 2 1 3 2 3 1 3 2 2 3 4 1 2 1 1 1 4 1 1 3 2 1 1 1 2 2 1 1
## [29161] 1 3 1 1 3 2 3 2 3 1 1 3 2 3 3 1 3 1 3 2 1 1 2 1 4 4 3 1 2 1 1 3 4 1 3 3
## [29197] 3 4 1 2 2 1 1 3 2 4 2 2 3 2 2 2 3 3 1 3 1 4 1 1 4 4 4 2 4 2 3 2 1 3 1 4
## [29233] 3 2 4 3 3 3 1 4 2 2 2 3 2 3 3 2 1 3 3 2 1 3 2 3 1 3 1 3 4 2 1 2 3 1 1 3
## [29269] 2 3 1 3 1 3 3 4 1 3 3 1 3 1 4 3 1 2 2 1 3 3 4 3 3 2 3 3 1 4 4 1 3 3 1 3
## [29305] 3 3 2 4 2 3 2 2 2 4 2 3 1 1 3 2 2 2 2 2 2 1 3 1 3 3 3 4 2 3 1 3 3 3 2 2
## [29341] 3 4 3 1 2 3 2 3 2 3 1 2 2 4 3 2 2 3 3 1 2 3 1 1 2 2 2 4 3 3 2 2 3 2 3 4
## [29377] 1 3 1 1 1 3 1 1 3 4 1 4 4 4 2 3 1 1 3 4 3 3 3 3 3 1 2 2 4 1 4 1 2 1 1 2
## [29413] 1 2 4 2 1 2 3 2 1 3 3 1 4 3 2 1 3 4 1 1 3 3 1 4 4 2 1 2 4 1 3 1 1 3 1 2
## [29449] 1 2 2 2 3 1 2 1 2 1 1 1 2 2 3 1 2 4 4 2 1 3 4 2 3 4 1 3 1 3 3 3 3 3 3 1
## [29485] 3 1 3 2 2 3 3 1 3 1 3 4 3 1 4 4 2 3 1 2 4 1 3 1 2 1 3 2 2 3 2 3 4 3 3 1
## [29521] 1 2 3 1 2 1 2 2 2 3 3 3 3 4 4 4 2 3 3 3 3 1 3 2 2 2 3 2 3 2 2 3 3 1 1 3
## [29557] 4 1 2 1 1 3 2 2 3 2 1 3 4 2 1 3 1 2 4 1 2 1 1 1 3 3 3 3 4 3 3 4 1 3 3 1
## [29593] 4 2 2 3 3 2 3 3 3 4 2 2 3 3 3 2 1 1 1 3 1 3 1 1 2 1 4 2 4 2 2 1 1 3 2 3
## [29629] 3 1 3 3 3 3 3 3 1 3 3 3 3 4 3 3 1 1 2 3 3 1 2 3 2 2 2 1 2 2 3 4 4 3 2 2
## [29665] 2 2 2 1 2 3 4 3 1 4 3 2 2 3 3 2 4 3 1 1 2 3 2 1 4 1 2 2 4 3 4 2 1 3 2 1
## [29701] 3 1 2 3 1 1 2 4 1 1 3 3 3 2 2 4 3 1 3 1 1 1 1 3 2 2 1 1 2 2 3 4 4 2 2 2
## [29737] 2 2 3 1 1 2 3 1 3 2 2 1 1 2 1 3 1 3 4 3 2 3 3 4 4 2 2 3 2 1 2 2 3 4 3 3
## [29773] 4 3 1 1 2 2 2 3 1 1 3 3 2 4 1 1 2 3 1 3 1 3 2 3 1 3 2 3 3 2 3 1 3 2 1 3
## [29809] 4 1 4 2 3 2 4 2 2 3 2 3 1 3 4 3 3 3 2 2 3 1 1 1 2 2 1 3 3 3 1 1 2 3 2 3
## [29845] 1 2 4 3 1 3 3 2 1 3 3 2 2 2 3 2 4 2 4 3 1 4 1 2 1 3 1 3 3 2 3 1 2 1 2 3
## [29881] 2 3 2 4 3 3 3 2 3 2 3 1 2 2 2 3 2 1 2 3 3 2 3 2 3 1 2 3 3 3 3 1 3 2 2 2
## [29917] 2 3 3 1 3 3 3 1 2 2 1 2 4 3 1 2 2 3 1 4 1 3 3 3 3 2 1 3 2 2 1 2 1 2 2 1
## [29953] 3 1 2 4 4 1 4 4 3 3 4 3 3 2 1 2 1 1 2 3 1 4 2 3 2 2 2 3 3 3 2 3 3 1 3 4
## [29989] 2 3 2 2 2 2 2 1 2 3 3 1 1 1 3 3 2 2 2 1 1 2 2 1 3 4 4 4 2 2 1 1 3 3 2 1
## [30025] 3 3 3 2 3 3 3 3 3 1 2 3 3 4 2 3 3 3 3 3 3 1 1 3 3 2 2 2 3 1 1 1 3 4 3 4
## [30061] 3 3 2 1 1 3 4 2 3 2 1 1 2 2 2 2 3 1 1 2 3 2 3 3 3 1 3 3 2 1 2 1 2 4 1 1
## [30097] 3 1 1 3 2 3 2 2 3 4 2 2 1 2 1 1 2 2 3 1 3 3 1 1 2 3 3 2 1 1 4 1 3 3 2 3
## [30133] 1 1 3 4 1 3 3 1 3 4 3 3 2 1 3 3 4 2 2 1 3 4 2 3 3 2 2 3 3 2 3 1 4 3 4 1
## [30169] 1 3 3 3 3 3 3 2 3 1 1 3 1 3 3 2 3 3 2 3 4 4 1 1 2 3 2 4 3 3 4 4 1 3 2 2
## [30205] 2 2 3 3 3 2 4 1 3 3 3 1 2 3 1 2 2 3 1 3 3 2 1 3 1 3 2 1 1 3 1 2 3 2 2 1
## [30241] 3 2 2 3 1 3 2 3 3 2 1 1 2 2 4 1 4 4 3 2 2 3 1 3 2 1 3 2 3 2 2 2 2 4 3 4
## [30277] 2 1 1 2 4 2 1 1 1 2 1 3 3 1 1 1 3 3 4 4 2 4 3 3 3 2 3 1 4 1 2 1 1 4 3 3
## [30313] 2 1 1 1 3 4 3 1 4 2 3 4 2 3 3 4 1 2 1 3 4 3 4 3 4 1 3 2 2 3 4 2 2 4 2 1
## [30349] 3 3 3 1 2 3 3 2 3 2 4 1 3 3 3 2 1 2 2 3 1 2 2 1 1 1 2 3 3 2 4 4 1 3 2 3
## [30385] 3 3 2 3 2 3 2 1 3 1 1 2 4 3 4 4 3 2 4 4 2 1 1 1 2 2 1 1 3 1 1 1 3 3 3 1
## [30421] 2 4 3 2 3 1 2 1 4 3 1 4 3 4 3 3 2 3 3 2 1 3 1 2 1 3 4 4 1 1 3 3 2 2 3 2
## [30457] 3 1 2 3 3 4 3 1 4 3 1 2 2 2 2 2 1 3 2 3 2 4 4 3 3 1 3 1 4 3 3 1 3 2 3 3
## [30493] 1 2 4 3 1 3 1 3 3 4 3 1 3 1 1 4 3 2 1 3 1 4 3 3 3 3 4 4 1 2 3 1 3 3 1 2
## [30529] 1 4 1 2 2 3 4 1 1 2 3 3 3 1 1 1 1 4 3 3 1 2 4 2 2 4 1 2 3 3 2 2 3 4 2 2
## [30565] 1 2 2 1 2 3 2 2 3 3 1 4 1 3 3 2 3 2 3 3 3 3 3 1 4 2 1 2 3 1 1 3 3 4 3 3
## [30601] 1 4 3 4 1 2 3 4 2 2 4 1 1 2 4 2 1 4 3 3 3 1 3 2 1 3 3 3 2 3 1 1 4 2 3 3
## [30637] 4 3 3 3 3 3 2 2 4 1 3 3 4 4 3 3 1 1 1 3 2 3 4 3 3 2 1 2 2 2 1 4 3 4 2 4
## [30673] 3 1 3 3 3 3 1 1 3 3 4 1 1 3 3 1 1 1 1 3 2 1 2 3 2 2 3 2 2 2 2 2 3 3 1 3
## [30709] 1 3 1 3 2 1 1 1 2 3 2 3 4 3 3 3 3 4 3 1 4 3 3 1 3 3 2 3 3 4 3 3 1 3 3 2
## [30745] 2 3 4 3 3 2 1 3 3 3 2 3 3 3 1 2 3 2 4 2 3 3 4 3 2 3 3 3 4 3 1 1 3 2 1 1
## [30781] 1 3 3 4 3 1 3 2 1 2 4 1 3 3 1 1 4 4 3 4 3 2 2 4 3 1 2 3 1 3 2 3 2 1 1 3
## [30817] 2 2 3 3 2 4 1 3 2 1 1 1 4 1 3 2 2 3 2 1 3 1 1 1 2 4 3 2 3 1 2 1 1 1 1 2
## [30853] 2 1 3 4 3 1 1 2 3 2 4 3 3 1 3 3 2 2 1 4 1 3 4 3 3 2 3 1 2 3 4 4 3 4 1 3
## [30889] 2 1 1 4 4 1 4 3 2 3 3 4 2 4 1 1 1 2 3 3 3 3 1 2 4 1 3 1 1 3 3 3 3 2 4 2
## [30925] 2 2 2 2 2 2 1 3 2 3 3 4 3 2 3 3 3 2 2 3 1 3 4 4 2 2 3 4 2 2 1 3 2 2 2 1
## [30961] 3 3 4 3 3 3 2 1 4 2 2 2 3 1 2 3 3 1 3 4 1 1 3 1 3 2 1 2 4 1 1 3 3 2 3 4
## [30997] 2 4 2 1 1 2 3 1 3 1 2 3 2 3 3 1 3 2 3 2 2 1 3 2 3 2 3 1 3 4 2 1 1 1 3 4
## [31033] 2 1 2 2 2 2 1 4 2 1 3 2 2 1 4 2 2 3 3 3 1 1 1 2 3 2 3 2 2 2 2 2 3 2 2 2
## [31069] 1 3 3 3 2 3 2 3 3 2 3 2 3 2 1 1 1 2 2 4 2 2 2 2 3 3 2 3 2 3 4 2 2 3 3 4
## [31105] 3 1 3 3 2 2 3 1 3 2 1 3 2 3 2 4 2 2 2 3 3 1 3 3 3 1 4 2 2 3 3 4 1 3 3 3
## [31141] 2 3 3 1 3 1 4 3 4 3 3 1 3 3 2 4 1 4 3 2 3 2 3 2 1 2 1 3 3 3 3 1 2 3 3 4
## [31177] 4 4 4 1 2 1 2 1 1 1 3 1 4 3 1 3 4 3 3 1 3 3 1 2 1 1 1 4 1 3 2 1 2 4 1 4
## [31213] 3 2 2 3 3 1 2 3 2 1 3 1 3 2 3 2 2 3 1 2 3 1 4 4 2 3 3 1 3 3 1 1 4 3 2 2
## [31249] 2 1 3 3 2 3 3 1 4 3 3 3 2 3 1 3 3 3 1 3 3 1 2 1 3 1 2 4 4 4 2 1 3 2 1 1
## [31285] 3 1 1 1 1 2 3 1 1 2 3 2 3 1 3 3 3 2 3 3 4 3 3 2 3 4 2 2 3 3 2 3 3 2 3 1
## [31321] 1 1 3 1 1 3 1 1 3 1 1 1 3 1 2 3 4 3 1 2 3 1 3 1 1 3 4 2 2 2 4 3 4 3 4 1
## [31357] 3 2 3 4 3 3 1 1 1 3 1 4 1 2 1 2 3 3 2 4 1 2 3 3 2 3 1 3 2 1 3 3 1 2 2 1
## [31393] 2 1 4 3 1 3 2 1 3 3 3 3 1 4 3 2 3 1 1 4 1 3 3 1 1 2 3 4 2 2 1 3 3 3 4 3
## [31429] 3 2 1 1 4 1 3 2 2 4 2 3 3 1 2 3 1 4 4 3 1 2 3 2 2 3 2 3 3 1 3 3 1 3 4 2
## [31465] 1 1 3 2 3 2 1 3 3 1 3 2 2 2 1 4 3 1 1 1 1 1 3 4 4 3 3 3 3 3 2 3 1 4 2 2
## [31501] 3 3 3 4 3 2 3 4 3 2 1 3 1 2 4 1 3 1 1 4 1 3 2 1 3 3 3 1 1 2 2 2 2 2 3 1
## [31537] 1 3 4 4 3 3 1 2 3 3 4 1 2 2 3 2 3 2 1 4 3 3 3 2 3 3 1 2 4 4 1 4 1 2 2 2
## [31573] 1 3 2 3 4 3 4 2 4 3 2 1 3 2 1 2 4 2 2 1 2 2 3 4 1 3 3 3 2 2 3 3 3 3 3 1
## [31609] 2 4 2 3 3 1 3 1 1 3 3 3 1 4 3 2 3 2 1 4 4 2 1 3 3 1 1 3 1 3 3 2 1 3 3 1
## [31645] 2 3 2 3 3 3 1 4 2 2 1 3 1 3 4 4 4 3 2 4 3 3 3 1 3 1 4 3 1 3 3 3 1 1 1 2
## [31681] 1 4 3 3 3 2 4 4 1 3 3 2 1 2 1 4 2 3 2 1 3 1 1 3 3 2 2 2 3 4 1 2 3 1 1 3
## [31717] 1 4 3 4 3 2 1 2 3 1 4 3 1 1 1 2 1 3 2 2 1 3 3 3 2 2 1 3 1 2 2 4 3 2 3 3
## [31753] 3 4 3 2 4 3 2 2 3 3 2 4 3 4 3 1 3 2 3 3 2 4 1 1 2 3 3 3 1 2 3 4 1 3 3 1
## [31789] 2 2 3 1 2 1 3 3 3 3 3 4 2 4 1 1 1 2 3 3 3 3 4 2 3 2 3 3 2 3 3 1 4 2 2 3
## [31825] 2 2 3 1 1 2 2 2 4 3 3 1 4 4 3 2 2 3 2 2 2 2 1 3 3 2 3 3 3 3 4 2 3 3 3 2
## [31861] 3 2 3 2 4 3 4 1 2 4 3 3 2 1 4 1 2 4 1 3 3 4 3 2 4 1 1 3 4 3 2 3 2 1 1 3
## [31897] 3 3 3 2 3 2 3 2 4 3 3 3 4 3 3 2 1 4 3 4 3 3 3 3 2 2 3 3 2 1 4 2 3 2 3 1
## [31933] 2 2 4 2 3 1 3 2 1 3 1 3 3 3 1 3 2 2 3 1 2 2 2 2 2 1 4 3 1 1 3 1 2 1 4 3
## [31969] 1 3 1 3 1 3 4 1 2 1 1 3 2 1 1 3 3 2 4 2 1 3 3 2 4 3 3 3 3 1 3 1 3 3 4 2
## [32005] 4 4 2 1 2 1 1 3 3 2 3 1 4 1 1 3 2 1 2 3 2 1 3 3 2 4 1 3 3 3 3 1 2 3 2 4
## [32041] 2 1 1 2 2 3 4 4 3 3 2 3 2 3 2 4 3 2 3 3 2 4 4 2 3 1 4 3 1 2 1 1 3 2 4 2
## [32077] 1 3 2 1 3 1 2 1 3 3 1 3 3 4 1 2 1 2 2 1 2 2 4 3 1 2 3 2 1 3 3 3 3 1 4 2
## [32113] 3 3 3 3 4 4 1 1 1 3 3 1 1 3 1 1 2 4 2 1 2 2 3 1 1 3 4 3 3 2 2 3 1 2 2 1
## [32149] 3 3 1 2 2 3 3 1 3 3 3 3 2 2 3 3 1 2 3 1 4 2 3 3 2 3 3 1 1 1 3 3 3 1 2 4
## [32185] 3 1 4 4 3 2 2 2 1 3 1 1 3 3 2 2 1 2 3 4 3 3 1 2 2 3 4 2 1 3 3 2 3 1 2 2
## [32221] 2 1 4 2 1 2 3 2 3 2 2 3 2 3 3 2 3 1 2 1 3 3 3 2 2 3 1 1 4 1 1 1 3 1 3 4
## [32257] 1 3 3 1 4 3 1 2 3 3 1 3 3 2 2 1 3 1 3 2 3 3 1 3 4 3 3 3 3 3 3 3 2 4 2 2
## [32293] 4 3 3 4 3 3 3 3 3 3 3 1 2 1 3 4 3 3 3 1 2 3 3 2 2 2 4 3 2 2 3 3 3 3 1 3
## [32329] 3 3 4 4 2 4 3 3 4 3 4 4 1 4 1 2 2 2 3 2 3 1 3 1 4 4 3 2 2 2 2 4 1 3 2 3
## [32365] 1 3 2 2 3 3 3 2 1 4 3 3 1 3 1 3 3 1 3 2 1 3 2 3 3 4 2 1 2 3 2 1 1 2 2 1
## [32401] 2 1 1 4 3 4 4 3 3 1 1 3 4 1 2 1 2 2 1 1 1 3 3 4 3 1 3 3 4 3 1 2 2 2 1 3
## [32437] 2 3 3 4 2 3 2 3 2 3 4 3 3 1 3 4 3 2 1 1 2 3 3 2 2 3 1 1 4 2 3 3 3 1 2 3
## [32473] 2 2 3 2 3 3 3 2 2 1 1 3 1 2 1 2 1 4 1 1 3 2 3 3 1 2 4 2 2 2 2 3 3 3 2 3
## [32509] 3 2 4 3 1 2 2 4 3 3 4 2 4 3 1 2 2 2 2 2 3 1 3 3 4 3 3 2 4 2 3 1 2 3 3 2
## [32545] 3 1 3 2 2 2 1 3 3 4 3 2 4 2 2 3 3 3 3 1 2 3 2 1 1 3 4 2 3 2 3 3 3 1 1 1
## [32581] 4 2 3 2 3 2 2 2 2 4 3 1 1 3 2 4 2 4 3 3 2 2 1 2 3 3 2 2 3 1 2 3 2 3 2 2
## [32617] 1 3 3 3 1 2 2 4 2 3 4 3 4 3 3 1 3 4 4 1 2 4 2 1 2 2 2 3 3 3 3 1 3 2 1 3
## [32653] 2 1 3 3 2 2 2 3 3 2 3 3 1 4 2 2 3 4 2 3 3 1 3 3 2 2 3 4 1 2 3 3 4 2 3 1
## [32689] 4 2 1 1 1 3 2 1 4 2 1 3 2 3 4 1 2 2 4 1 1 3 3 3 2 2 3 2 4 4 3 4 3 1 3 3
## [32725] 1 3 2 4 3 4 3 3 3 3 4 1 3 3 1 2 2 3 3 4 1 3 1 3 4 3 2 4 2 3 2 4 3 4 2 4
## [32761] 3 2 2 2 4 1 3 3 2 2 2 2 3 2 2 1 4 1 1 2 1 3 1 3 3 3 1 2 1 4 3 2 3 3 2 2
## [32797] 2 3 2 3 1 2 2 1 3 2 1 3 3 4 3 3 4 3 1 2 1 3 1 1 1 3 4 3 2 2 3 3 3 4 3 2
## [32833] 1 1 4 4 3 3 4 3 4 3 1 3 4 3 2 3 2 1 3 2 2 1 1 2 1 2 1 1 2 3 4 1 2 3 3 2
## [32869] 3 1 4 2 1 4 4 2 4 3 1 3 2 3 3 1 3 3 3 3 2 2 3 2 3 3 3 3 1 2 1 1 2 2 1 4
## [32905] 3 3 2 1 2 2 3 3 2 2 3 2 2 2 2 3 1 3 4 4 2 2 2 3 4 3 3 1 1 2 3 3 3 4 3 1
## [32941] 3 3 4 2 4 3 3 2 2 3 3 4 2 3 3 1 2 3 2 3 3 1 3 2 4 1 3 3 2 1 2 3 4 3 3 2
## [32977] 1 2 2 2 2 3 3 1 1 3 1 1 1 1 3 1 1 2 4 3 3 2 3 4 1 3 2 3 3 2 2 3 3 1 3 1
## [33013] 3 1 1 2 1 1 3 2 3 4 1 4 4 3 3 1 4 4 4 2 3 3 2 3 1 2 2 3 3 4 3 1 2 3 3 1
## [33049] 2 3 1 2 2 3 3 2 3 1 2 2 4 1 3 3 3 3 4 3 2 1 2 3 1 3 1 4 1 4 3 3 4 3 2 3
## [33085] 2 1 3 3 3 4 1 3 1 1 3 1 1 1 2 3 2 3 4 1 2 2 3 3 1 1 3 3 3 3 2 1 3 3 4 1
## [33121] 4 2 1 3 2 3 3 2 3 3 3 2 3 1 3 4 3 4 1 4 3 4 3 2 3 1 1 2 4 1 1 4 1 2 3 2
## [33157] 1 4 3 1 3 3 3 1 1 3 3 3 4 1 1 1 2 1 1 3 2 2 2 3 4 2 2 2 2 3 1 4 1 2 3 3
## [33193] 2 3 3 2 3 2 4 2 3 1 1 3 3 1 1 1 3 1 4 3 1 3 1 4 3 2 2 3 2 1 2 3 1 1 3 3
## [33229] 3 2 3 1 3 2 3 3 4 3 2 3 1 1 3 4 3 2 1 4 1 1 3 2 4 3 4 3 3 1 3 3 2 4 3 4
## [33265] 2 2 1 2 3 1 3 3 4 3 4 3 1 2 1 4 2 1 4 2 4 2 2 1 4 1 1 3 2 2 3 1 3 3 4 4
## [33301] 2 1 4 2 3 4 1 2 1 1 2 3 1 1 4 3 2 1 3 2 2 3 3 2 1 1 1 3 4 3 1 3 3 3 1 2
## [33337] 4 2 3 1 4 4 2 1 3 2 3 2 3 3 3 2 4 1 2 1 1 3 2 3 1 1 3 3 2 3 3 1 3 3 2 3
## [33373] 2 2 2 3 2 2 3 4 3 4 2 2 3 3 2 2 1 3 2 2 3 1 1 3 3 1 4 3 3 1 1 1 1 2 4 2
## [33409] 3 4 1 2 3 2 3 3 3 3 4 3 3 2 1 2 1 1 3 3 2 3 2 1 4 3 4 3 2 2 4 3 4 2 1 2
## [33445] 4 1 2 1 3 1 1 3 1 3 1 1 1 1 4 3 3 2 4 2 1 2 3 3 4 4 4 3 2 3 3 1 3 4 2 4
## [33481] 1 1 3 1 3 3 1 2 2 2 3 1 3 1 1 4 3 3 3 2 2 2 3 3 4 4 3 1 1 1 4 1 3 1 3 3
## [33517] 4 3 3 4 1 4 3 1 3 3 2 3 3 3 2 1 1 3 3 3 3 3 4 3 2 1 3 4 1 1 1 1 1 2 1 3
## [33553] 1 3 2 3 2 4 3 3 2 3 3 1 4 2 4 3 2 3 3 2 4 1 2 2 3 3 1 2 3 2 3 1 3 2 4 1
## [33589] 3 4 1 2 2 2 1 3 2 3 1 2 3 3 1 1 3 3 1 4 1 3 1 2 1 3 4 2 3 4 3 2 1 3 3 3
## [33625] 3 3 2 2 1 3 3 1 2 3 3 3 2 4 1 2 3 3 3 4 2 2 3 4 2 3 3 3 4 2 4 2 3 3 2 1
## [33661] 4 3 1 3 1 2 1 2 2 2 1 1 3 4 3 1 4 3 2 3 2 3 2 3 2 1 1 3 1 2 1 2 4 1 3 3
## [33697] 2 3 2 3 2 3 1 1 2 4 4 1 4 3 3 2 3 1 3 4 3 3 3 2 4 1 2 3 3 3 4 3 4 1 3 2
## [33733] 2 2 3 2 4 1 3 4 3 1 3 3 1 2 1 3 1 4 1 3 3 4 2 1 4 1 3 3 3 2 3 2 4 1 3 2
## [33769] 1 3 2 1 1 3 2 3 3 2 4 3 3 3 4 1 1 2 2 1 3 3 4 1 2 4 4 2 1 3 1 1 4 3 2 3
## [33805] 1 1 2 3 4 1 1 2 1 1 3 2 2 3 3 4 1 1 3 3 3 2 1 3 4 3 2 3 3 2 3 1 2 2 2 3
## [33841] 2 2 1 3 4 3 1 2 1 3 3 3 4 1 2 3 3 3 1 2 3 2 3 3 3 1 1 2 4 1 2 1 3 3 2 1
## [33877] 4 3 1 1 1 3 3 3 2 3 2 4 3 3 2 2 4 1 1 3 1 3 2 3 4 3 4 1 4 3 1 1 4 3 4 3
## [33913] 2 2 1 4 4 4 4 3 1 2 3 2 3 4 3 1 2 3 1 2 3 2 1 3 2 4 1 3 2 3 3 2 2 2 3 3
## [33949] 3 2 2 1 3 3 3 3 1 3 2 3 3 3 1 2 3 1 2 2 3 3 4 1 4 3 3 3 3 2 1 2 4 2 1 2
## [33985] 4 4 2 3 3 2 2 3 3 4 2 2 2 1 3 3 3 3 1 1 1 1 4 3 1 3 3 2 3 3 1 1 1 3 2 2
## [34021] 1 3 3 2 2 4 3 2 3 4 2 4 3 1 1 4 1 4 2 3 2 1 3 1 1 2 3 2 2 3 2 2 3 2 3 2
## [34057] 1 3 3 3 3 3 1 1 4 1 2 3 3 1 3 2 3 3 3 2 3 2 1 2 4 2 1 1 3 1 3 2 4 3 2 4
## [34093] 2 4 3 4 3 1 3 3 2 1 1 3 3 4 2 3 3 2 4 4 1 3 3 3 1 1 4 1 1 1 1 2 1 1 2 2
## [34129] 4 2 1 3 2 3 3 4 3 2 3 2 2 3 1 2 3 4 1 4 1 1 3 3 3 3 2 1 4 3 1 1 3 2 1 3
## [34165] 3 4 3 3 1 2 2 3 1 3 1 2 1 1 4 1 3 2 3 2 2 2 3 4 4 1 2 4 3 2 3 2 3 3 3 3
## [34201] 1 3 2 1 1 1 2 3 2 3 1 1 3 1 1 3 2 2 1 4 2 2 1 1 2 3 3 2 3 3 3 3 4 4 4 1
## [34237] 3 3 2 4 3 2 1 1 1 3 3 3 3 3 3 4 1 2 3 1 2 3 2 1 2 1 3 2 4 1 2 4 3 3 3 1
## [34273] 1 3 1 1 1 3 2 3 2 3 4 1 3 2 1 2 3 1 3 1 1 3 2 2 1 4 1 2 3 3 2 4 1 2 1 1
## [34309] 3 1 3 3 1 2 1 1 1 1 4 3 3 3 3 1 4 3 2 1 3 2 3 2 4 2 2 2 4 2 2 2 3 2 1 2
## [34345] 4 4 1 3 3 2 1 1 3 3 1 3 2 3 2 3 2 1 3 1 1 2 1 2 1 3 1 3 2 4 3 1 2 3 3 2
## [34381] 1 3 3 3 4 1 1 1 2 2 2 1 3 4 3 3 3 3 2 3 1 1 1 4 4 3 4 2 4 2 2 2 3 2 3 3
## [34417] 3 4 3 3 4 3 1 3 2 3 3 1 1 2 2 4 3 1 2 3 3 1 3 2 4 3 3 2 1 4 3 1 2 1 3 2
## [34453] 1 3 2 1 2 3 2 2 2 1 3 4 3 2 2 3 3 3 1 2 1 3 1 2 3 4 1 3 2 3 3 4 4 1 3 3
## [34489] 3 3 3 1 3 1 3 1 2 1 3 3 3 2 2 3 1 2 2 3 3 3 1 2 1 1 3 3 1 4 2 1 1 4 3 2
## [34525] 1 1 2 3 2 1 1 3 3 3 2 3 3 3 4 2 3 3 2 1 1 3 2 3 3 3 2 2 3 3 4 4 2 3 3 1
## [34561] 3 3 4 3 2 2 1 3 4 2 3 2 2 2 3 3 2 4 3 3 2 2 4 3 3 3 1 3 3 3 3 3 3 1 3 1
## [34597] 3 3 3 4 1 2 2 2 2 2 3 1 3 2 2 3 1 4 3 2 2 1 2 2 3 2 3 1 2 4 2 4 2 4 2 3
## [34633] 3 2 3 3 4 2 2 3 2 1 1 4 1 3 4 3 4 3 3 1 2 2 3 2 3 4 1 3 3 3 2 1 3 1 2 2
## [34669] 3 2 1 3 4 1 1 2 2 1 4 1 2 1 3 3 3 4 1 3 2 1 1 3 2 1 1 2 3 3 3 1 3 3 4 3
## [34705] 3 2 3 3 4 4 4 2 3 3 3 3 3 1 3 1 4 3 2 3 2 4 3 2 3 3 1 1 4 2 3 1 4 3 2 3
## [34741] 2 2 1 3 1 3 3 3 3 3 4 1 2 2 1 3 3 3 1 4 2 1 3 3 1 2 1 1 3 3 2 3 1 3 3 2
## [34777] 2 1 3 3 3 1 1 3 1 2 3 1 3 1 1 4 2 4 2 2 1 2 3 3 1 3 2 2 1 2 1 3 3 1 3 3
## [34813] 3 1 3 1 2 4 3 4 3 1 3 3 1 2 1 3 3 1 4 4 3 2 1 4 3 3 4 4 3 1 3 1 1 1 2 1
## [34849] 1 3 2 2 2 3 2 3 2 2 3 2 3 1 2 2 2 1 3 3 1 1 3 2 3 3 2 1 4 1 2 3 1 3 3 1
## [34885] 3 3 3 2 3 3 1 3 2 1 1 3 4 4 3 3 4 3 1 3 1 1 1 2 2 3 4 2 1 4 4 1 1 3 3 1
## [34921] 2 3 2 3 3 1 3 3 2 3 2 4 1 3 2 3 3 2 3 3 2 1 3 3 1 2 2 3 2 2 3 4 2 3 2 4
## [34957] 3 3 3 2 4 3 3 3 3 3 4 2 2 3 3 3 1 2 2 4 4 1 2 1 1 2 2 2 2 2 1 3 1 3 1 1
## [34993] 1 3 1 2 3 4 3 4 3 4 3 3 1 4 3 1 1 1 3 1 2 2 2 3 2 2 3 2 4 3 1 3 4 1 3 2
## [35029] 2 4 2 2 2 1 2 2 3 2 3 3 3 3 3 2 3 3 2 2 4 3 3 1 4 4 1 4 3 4 1 3 3 2 3 3
## [35065] 4 2 1 1 1 3 3 2 3 3 2 1 1 2 2 4 4 3 2 3 3 1 1 1 4 3 1 3 3 3 2 2 4 1 3 3
## [35101] 2 1 2 1 3 1 3 3 3 3 4 4 1 4 1 3 3 4 3 2 1 3 2 4 3 3 3 2 3 3 1 4 1 1 2 3
## [35137] 1 1 2 2 3 3 4 1 3 1 1 2 3 3 1 3 1 3 4 3 1 2 1 1 1 1 1 1 1 3 4 3 3 2 3 4
## [35173] 3 2 4 3 1 3 3 1 3 2 3 1 1 2 2 3 3 4 4 4 1 1 3 2 4 1 2 1 3 3 2 2 2 1 2 3
## [35209] 3 3 3 3 2 3 3 3 4 2 1 2 4 2 2 4 2 4 3 2 1 2 1 3 2 2 2 1 1 3 4 3 4 3 3 2
## [35245] 1 3 3 3 3 4 4 1 3 1 2 4 2 3 1 3 3 3 3 3 3 4 1 4 2 3 2 2 1 1 2 3 3 4 4 3
## [35281] 3 1 1 1 3 1 3 1 1 3 3 2 3 2 3 1 3 1 3 1 3 3 2 3 3 1 1 1 1 2 3 2 1 1 2 4
## [35317] 3 3 1 2 2 1 3 3 3 2 3 3 2 2 2 1 3 3 3 4 3 4 1 2 1 3 1 3 1 2 3 3 1 2 3 3
## [35353] 2 2 4 2 3 2 3 3 2 3 3 4 4 4 2 1 2 2 4 3 4 2 3 3 1 3 3 1 3 3 1 1 2 2 2 3
## [35389] 1 1 1 1 4 3 2 3 4 2 3 3 1 2 3 3 2 2 1 3 2 3 1 3 4 2 1 4 4 3 4 3 3 2 2 4
## [35425] 4 2 4 3 3 1 3 3 4 1 2 3 3 1 1 1 4 4 2 1 1 3 3 4 3 3 3 4 3 2 1 4 2 2 2 3
## [35461] 3 3 4 1 2 3 3 3 4 3 4 3 3 1 1 2 3 3 3 1 3 1 4 2 1 1 3 1 3 2 2 4 2 2 3 4
## [35497] 2 1 3 3 1 3 3 1 2 4 1 2 1 4 3 1 2 2 3 1 3 3 3 1 3 1 2 3 1 1 1 4 3 3 4 2
## [35533] 4 1 4 3 3 3 3 3 4 3 3 1 1 3 1 2 1 3 3 3 4 2 1 4 3 1 3 2 3 3 2 1 2 3 2 1
## [35569] 3 1 1 3 3 3 2 1 3 3 3 2 4 3 3 4 2 1 3 3 1 3 4 1 3 3 2 1 3 3 4 2 3 3 2 2
## [35605] 1 3 3 3 4 3 2 2 3 3 1 3 3 2 4 4 4 1 3 1 1 2 3 3 1 1 2 3 3 3 2 1 3 1 3 2
## [35641] 2 3 1 3 3 4 2 4 1 1 1 3 1 3 4 3 1 3 3 2 1 1 1 3 3 2 3 3 3 1 1 2 3 3 3 3
## [35677] 4 3 2 1 1 1 3 3 3 3 3 2 4 3 4 2 3 2 1 3 4 1 2 3 2 3 4 2 1 2 3 2 4 3 3 3
## [35713] 2 3 1 1 2 4 3 3 3 1 3 1 1 2 2 2 3 3 4 3 1 3 3 3 3 3 3 2 2 3 1 2 1 1 4 3
## [35749] 1 3 1 3 2 2 3 1 3 2 2 2 2 3 4 1 1 2 3 4 1 1 3 4 1 1 2 3 4 3 1 1 2 3 3 1
## [35785] 3 3 3 1 4 3 1 1 4 2 1 4 4 2 3 4 4 1 2 4 1 4 3 4 1 3 2 2 3 4 1 2 2 1 1 2
## [35821] 2 3 1 3 2 1 3 3 3 2 2 3 3 1 3 4 2 1 3 2 3 2 1 2 4 4 3 3 3 4 2 3 3 2 2 3
## [35857] 3 1 4 1 3 1 3 3 3 4 3 1 2 2 4 3 3 2 4 3 3 1 4 4 3 1 2 1 3 1 2 2 2 3 3 3
## [35893] 2 4 4 1 1 2 4 2 3 2 4 2 3 1 2 3 1 3 3 3 2 3 3 4 3 1 4 4 1 3 3 3 3 1 3 3
## [35929] 1 3 1 4 2 1 3 4 2 2 3 1 3 4 3 3 1 4 1 2 2 1 1 4 2 3 3 3 3 1 1 1 1 1 1 4
## [35965] 3 1 3 4 1 4 2 4 1 3 1 2 1 3 1 2 2 3 3 1 3 3 3 1 3 1 2 3 2 1 4 3 1 3 1 3
## [36001] 1 4 3 1 2 3 1 2 1 4 4 3 3 1 3 2 1 2 3 3 3 2 3 4 1 2 3 1 1 3 2 2 4 2 3 3
## [36037] 2 2 3 2 4 3 1 2 1 1 3 4 2 3 1 2 3 1 3 4 4 2 4 2 3 1 2 2 1 1 4 1 3 1 3 1
## [36073] 4 1 2 3 3 3 4 2 3 2 1 3 1 4 4 1 1 2 3 4 1 3 1 3 2 1 4 1 2 3 2 3 3 4 1 3
## [36109] 2 3 1 1 3 4 1 1 2 3 3 1 4 1 1 2 3 2 3 2 2 4 1 3 3 2 3 4 2 3 2 4 2 3 2 4
## [36145] 3 2 1 4 3 2 3 2 2 4 3 2 4 1 2 3 1 2 1 1 2 4 3 1 4 3 2 3 4 1 3 2 3 4 2 2
## [36181] 3 2 1 3 4 1 3 2 3 2 2 2 1 2 3 3 1 3 3 2 2 1 3 3 1 2 2 3 1 3 2 2 3 3 2 3
## [36217] 2 4 1 1 1 2 2 2 1 1 3 1 3 3 1 3 3 4 2 1 3 2 4 2 3 3 3 3 4 1 2 3 3 3 3 2
## [36253] 3 3 2 2 3 2 4 1 2 1 3 2 3 3 2 3 3 4 3 2 3 2 1 3 3 1 3 3 1 4 3 2 2 1 4 2
## [36289] 3 3 3 3 1 3 1 3 2 3 2 3 3 2 2 3 3 1 3 2 1 3 3 2 2 2 1 3 1 1 3 3 4 1 4 3
## [36325] 2 3 3 3 3 3 3 1 3 2 2 3 3 3 3 2 3 2 3 3 2 1 2 2 3 1 1 2 2 3 3 3 3 2 1 3
## [36361] 3 3 2 1 1 1 2 4 3 2 3 1 4 1 2 3 3 4 2 1 3 2 3 4 3 4 3 1 1 3 2 4 2 2 3 2
## [36397] 2 4 2 3 3 1 3 3 1 2 3 3 2 3 3 3 2 1 1 3 3 1 1 2 4 3 4 2 3 2 3 3 3 3 3 1
## [36433] 2 3 2 3 2 2 1 2 3 1 4 4 2 3 3 3 1 1 3 2 3 3 2 3 3 2 3 4 3 2 1 3 1 3 4 1
## [36469] 1 1 2 1 3 1 3 2 1 3 2 2 2 3 1 4 3 1 1 1 1 4 1 3 3 2 3 3 3 4 1 3 3 3 2 3
## [36505] 1 3 4 3 1 4 4 1 1 3 2 3 1 4 1 3 2 3 2 1 2 3 4 4 2 1 3 1 3 3 2 4 1 2 1 4
## [36541] 4 1 3 1 3 1 2 1 1 2 4 2 3 1 3 3 1 1 3 2 3 4 1 3 3 3 3 1 1 1 3 3 3 2 4 1
## [36577] 1 2 3 4 2 3 1 1 3 1 2 3 3 1 3 1 2 3 2 2 1 1 3 3 2 3 3 1 1 2 2 1 1 3 4 3
## [36613] 2 3 2 2 3 1 3 3 1 1 3 1 3 2 4 2 2 2 3 2 3 2 3 1 3 1 1 1 3 4 3 3 3 3 3 3
## [36649] 2 3 1 2 2 2 1 4 2 2 3 3 4 4 3 2 3 4 3 1 2 2 2 3 3 2 3 4 4 1 1 2 1 2 4 3
## [36685] 3 3 2 1 4 2 3 2 1 3 3 3 2 3 3 3 4 3 3 3 3 2 3 3 2 1 3 3 1 3 4 2 4 1 3 2
## [36721] 1 3 3 3 3 2 2 2 2 4 2 3 1 1 4 1 2 2 3 4 2 3 3 2 1 1 1 2 4 3 1 1 3 3 3 4
## [36757] 3 3 2 3 1 3 1 2 3 3 2 1 4 2 3 1 1 4 3 3 2 3 2 3 3 3 2 1 1 3 1 3 2 1 3 1
## [36793] 2 3 3 3 2 3 3 3 2 3 2 1 4 2 1 2 1 2 1 3 4 3 1 1 2 3 3 1 3 2 2 3 3 2 3 3
## [36829] 3 2 3 3 1 1 1 3 3 1 1 1 3 1 4 3 2 4 4 2 1 3 3 4 1 1 1 3 3 4 2 1 3 2 2 2
## [36865] 3 3 4 3 3 3 4 1 2 1 3 2 1 3 2 2 3 3 2 3 2 3 3 2 3 3 1 1 2 3 4 3 1 3 3 2
## [36901] 2 3 3 2 3 3 2 3 1 3 4 1 2 3 1 3 4 1 2 4 3 1 3 3 3 4 2 1 1 4 2 3 3 3 1 3
## [36937] 1 3 2 4 4 3 2 1 4 3 1 3 2 4 1 4 3 4 2 4 2 3 2 4 4 4 4 4 1 1 3 1 3 4 3 2
## [36973] 3 1 4 1 4 3 2 2 4 3 4 1 1 1 2 3 4 2 1 2 3 4 3 3 2 1 4 3 2 3 4 2 1 4 3 3
## [37009] 3 3 2 3 1 3 2 3 4 2 3 1 4 1 3 3 3 4 3 3 3 2 1 1 3 3 4 2 4 4 1 1 3 3 4 1
## [37045] 3 2 1 4 4 3 3 1 2 3 2 1 3 2 3 4 2 3 4 1 2 1 3 2 3 3 2 3 1 2 2 2 2 3 1 3
## [37081] 2 3 1 3 2 3 2 2 1 2 2 3 1 2 3 3 4 3 3 4 2 3 1 1 3 3 1 2 2 1 3 1 3 2 3 2
## [37117] 1 3 3 3 2 1 3 2 4 4 1 1 1 4 1 2 2 4 3 1 3 1 3 3 3 3 3 4 3 1 3 3 3 2 3 2
## [37153] 4 4 4 1 3 4 1 2 3 1 3 1 3 1 4 4 3 3 3 3 2 4 4 1 1 3 2 4 4 2 3 1 3 1 3 3
## [37189] 3 4 3 3 3 3 4 2 1 3 4 2 3 1 1 1 3 4 3 4 3 2 1 3 4 1 3 3 2 3 3 4 2 2 3 3
## [37225] 2 1 1 3 3 2 2 2 1 3 3 3 1 3 3 1 3 3 3 2 4 2 3 4 2 1 2 2 1 3 1 2 3 1 2 3
## [37261] 2 3 3 3 1 2 4 2 3 4 2 3 2 1 4 4 3 3 1 2 2 2 2 2 1 2 1 4 2 3 3 2 3 3 1 3
## [37297] 3 3 2 3 4 1 2 1 1 3 2 3 2 4 1 1 2 2 3 2 1 3 3 2 3 1 3 3 3 1 3 1 3 3 1 4
## [37333] 4 4 3 3 2 3 4 2 3 2 3 1 2 3 1 1 2 2 3 1 3 3 3 3 3 2 1 4 3 4 1 3 4 3 2 1
## [37369] 3 3 4 4 1 3 3 2 3 2 1 2 3 1 2 3 3 3 1 3 2 3 1 3 4 4 3 1 1 3 2 4 3 4 1 2
## [37405] 1 2 3 3 2 3 1 4 2 2 2 2 1 4 2 3 2 2 2 3 4 1 3 2 4 1 3 3 2 3 3 4 3 3 4 4
## [37441] 3 3 2 2 3 3 4 1 3 3 4 1 3 1 2 1 1 1 1 3 1 2 3 2 3 1 2 1 2 3 4 3 1 4 3 3
## [37477] 3 2 3 2 1 4 3 1 3 2 2 3 4 2 3 3 4 1 2 4 2 1 2 3 1 4 1 1 3 3 1 3 1 1 3 2
## [37513] 1 1 1 4 2 1 4 3 3 1 2 2 3 2 1 3 1 3 3 2 1 3 2 2 1 2 3 1 3 3 3 3 2 3 3 2
## [37549] 2 3 3 4 1 2 3 1 2 2 1 4 3 1 2 2 1 2 2 2 2 4 3 1 3 2 4 2 3 3 1 3 2 3 4 2
## [37585] 2 4 4 2 3 3 4 1 3 3 2 4 4 2 2 4 3 1 3 2 1 3 1 2 3 4 2 1 2 4 3 3 4 3 4 3
## [37621] 3 1 2 3 1 4 4 4 3 1 3 3 1 3 2 3 3 3 3 2 1 3 3 2 2 1 3 1 4 3 4 3 1 3 3 3
## [37657] 3 1 4 3 1 2 1 3 1 3 3 1 1 3 3 2 4 3 1 2 3 1 3 2 4 2 3 3 2 3 4 3 2 1 4 3
## [37693] 1 2 3 3 2 2 3 3 1 3 4 2 1 4 4 3 3 1 3 2 4 4 3 1 1 4 3 1 1 1 1 1 3 3 3 2
## [37729] 2 4 4 2 3 2 1 2 1 3 3 3 1 1 4 2 3 1 1 1 3 3 2 4 1 4 1 3 3 3 3 1 4 1 2 3
## [37765] 3 3 1 2 1 3 3 4 2 3 2 1 3 2 3 3 2 2 2 2 3 2 3 1 2 3 2 2 4 3 3 3 3 1 2 3
## [37801] 1 3 2 2 3 3 3 1 4 2 2 2 2 3 3 4 3 4 2 1 2 3 1 3 2 2 3 1 2 3 1 2 2 2 3 4
## [37837] 2 2 2 3 3 1 3 3 2 3 2 4 4 1 3 3 3 3 4 2 4 3 1 3 1 3 4 2 3 1 4 3 3 3 4 1
## [37873] 3 4 1 2 3 1 4 3 3 3 3 4 4 1 4 2 3 4 1 4 3 2 3 3 2 2 2 2 1 2 1 2 4 3 3 4
## [37909] 1 3 1 4 4 1 1 1 3 3 3 2 3 3 3 1 3 1 1 1 2 4 3 2 3 3 3 1 2 1 2 2 1 3 1 3
## [37945] 3 4 4 2 2 1 3 4 3 3 4 1 2 3 3 2 2 2 3 3 3 3 4 2 3 4 1 4 3 3 1 2 1 4 2 4
## [37981] 2 2 4 1 2 1 2 4 3 1 2 2 1 4 1 1 4 3 3 2 3 2 2 3 3 2 3 3 3 2 3 2 1 3 2 2
## [38017] 1 2 3 1 3 3 1 2 1 1 1 1 3 2 4 4 2 3 3 1 4 2 2 3 2 2 3 4 2 4 2 4 2 3 1 1
## [38053] 3 1 2 2 4 2 3 1 2 1 1 3 3 3 2 1 2 2 2 3 2 3 2 2 3 2 1 1 3 3 3 4 3 1 1 2
## [38089] 3 3 1 1 3 3 2 3 1 2 4 3 4 3 2 2 4 4 3 3 2 2 1 2 1 2 2 1 3 3 2 3 3 1 3 3
## [38125] 2 1 2 4 3 1 3 1 4 2 2 3 1 3 2 4 3 3 4 1 3 1 3 4 1 2 2 4 1 2 1 3 4 3 1 4
## [38161] 3 2 4 2 1 3 1 2 4 1 3 1 3 1 2 1 3 3 2 3 2 2 3 2 1 3 3 3 3 1 4 2 3 2 1 2
## [38197] 2 1 3 3 4 4 3 3 3 4 2 3 3 3 3 3 3 1 1 2 2 1 3 3 3 2 3 3 3 3 2 3 1 1 2 4
## [38233] 2 3 1 1 3 2 3 1 2 1 1 2 2 3 2 3 3 2 2 4 2 1 4 1 3 3 4 1 2 3 4 3 2 2 3 3
## [38269] 3 1 4 2 3 2 3 2 3 3 1 3 1 3 3 3 2 4 1 4 3 3 2 4 1 1 2 3 1 2 1 3 3 4 2 2
## [38305] 4 2 3 3 3 3 4 1 1 4 3 1 3 1 4 1 3 3 3 3 3 4 3 3 4 2 3 4 3 2 3 2 3 1 1 2
## [38341] 2 2 4 3 1 3 1 3 3 2 3 3 2 1 3 4 1 2 2 2 1 3 4 1 3 2 1 4 4 1 3 2 2 3 3 1
## [38377] 3 3 2 3 3 1 2 3 2 3 1 2 4 1 1 1 3 2 2 1 2 4 3 1 1 2 1 1 3 1 2 4 3 3 3 2
## [38413] 2 1 2 2 1 2 2 1 2 1 2 4 4 4 3 3 3 3 2 1 2 1 2 3 1 1 3 1 2 3 3 2 2 3 3 1
## [38449] 2 4 1 1 3 1 3 3 1 3 3 2 4 3 1 2 4 3 2 2 1 2 3 2 2 3 3 3 3 1 3 4 3 2 3 4
## [38485] 2 3 4 1 1 3 2 3 2 2 4 2 1 4 2 1 3 3 1 2 3 4 4 1 4 2 4 2 3 1 2 3 2 4 3 2
## [38521] 3 3 3 3 2 1 1 1 3 1 4 2 2 3 3 3 2 1 3 1 3 4 3 1 3 2 2 3 1 2 2 3 1 1 3 2
## [38557] 1 3 1 1 3 3 2 1 3 3 1 3 1 3 1 2 1 3 1 3 2 3 3 2 2 1 3 2 2 3 4 2 3 3 1 4
## [38593] 3 1 2 3 3 1 1 3 2 3 1 2 1 2 3 4 1 4 3 4 3 3 4 2 1 1 1 1 1 2 4 3 2 3 1 2
## [38629] 4 1 3 3 1 3 1 2 4 3 4 1 3 3 2 1 3 2 2 3 3 1 4 3 3 3 2 1 4 2 3 1 3 3 3 1
## [38665] 2 2 3 2 3 1 3 2 3 2 2 1 2 3 3 3 3 3 1 1 3 2 3 3 3 3 3 3 1 1 4 3 3 4 3 3
## [38701] 2 3 1 2 3 4 3 4 3 1 2 4 1 3 3 2 2 3 1 3 2 1 3 2 3 3 3 4 2 3 1 1 1 3 1 1
## [38737] 1 4 3 4 1 1 2 3 1 2 3 2 3 3 3 3 1 3 2 2 1 1 2 3 2 2 4 4 4 3 1 3 2 3 1 2
## [38773] 1 4 3 3 1 2 3 1 4 3 3 2 4 3 3 3 1 2 1 1 2 1 1 2 2 4 3 2 2 2 2 3 4 3 4 3
## [38809] 2 1 1 1 1 4 3 2 2 2 3 3 4 3 1 4 2 2 3 4 2 3 3 3 3 1 1 3 2 3 2 3 2 1 1 3
## [38845] 2 3 3 2 1 3 2 3 3 4 1 4 1 3 3 3 1 3 1 2 3 3 1 3 1 2 4 1 2 4 1 4 3 1 2 1
## [38881] 3 3 4 2 4 4 1 3 3 3 1 2 3 3 3 3 3 3 3 2 3 2 3 4 3 3 1 2 3 1 1 1 1 4 2 2
## [38917] 4 3 2 1 2 1 2 1 4 3 3 3 1 1 1 3 2 3 4 3 1 3 2 3 3 4 2 1 2 4 3 1 2 3 2 3
## [38953] 3 1 2 4 2 1 4 3 3 2 3 3 1 3 3 1 3 3 1 2 3 3 1 4 3 2 2 1 2 3 2 2 2 3 1 1
## [38989] 3 3 1 1 2 3 4 4 1 3 2 2 2 3 2 3 3 4 2 1 1 1 3 2 3 4 1 2 4 2 3 2 1 3 2 3
## [39025] 3 2 2 1 4 3 3 2 1 4 2 3 4 4 1 1 2 1 3 2 3 2 3 2 4 3 2 3 4 2 3 3 4 1 2 1
## [39061] 3 4 1 2 3 1 1 2 1 2 3 1 3 2 1 1 3 1 1 3 3 3 3 1 4 3 2 1 4 1 3 1 3 2 3 3
## [39097] 3 2 2 1 4 1 1 3 3 4 3 2 2 4 3 1 2 2 3 1 1 1 3 1 3 2 4 2 4 1 3 3 3 1 2 1
## [39133] 1 3 1 1 4 2 1 3 2 4 2 3 4 3 2 3 3 3 3 2 4 3 1 4 1 3 3 2 2 4 3 1 4 1 1 1
## [39169] 4 3 2 4 1 3 1 2 3 1 3 1 3 3 3 3 3 3 1 1 3 2 2 2 3 2 2 3 1 1 2 3 3 1 3 4
## [39205] 2 3 1 2 3 1 3 1 1 2 3 2 3 3 3 3 2 2 3 4 3 3 2 4 1 3 4 3 3 2 3 3 3 3 2 1
## [39241] 4 3 3 3 1 3 1 3 3 3 3 4 3 2 4 2 3 1 2 2 1 4 2 3 2 1 4 3 4 2 3 3 1 2 2 3
## [39277] 4 2 1 3 4 3 1 3 4 3 3 3 4 3 3 1 3 2 3 4 4 1 3 3 1 4 2 3 2 3 2 2 2 2 4 1
## [39313] 3 4 3 3 3 2 3 2 1 4 3 3 1 3 4 3 3 2 1 2 3 1 2 1 3 1 4 2 3 2 1 3 4 4 3 1
## [39349] 4 3 1 3 3 3 3 3 3 1 2 2 3 4 1 1 2 3 4 3 3 2 1 3 2 2 2 1 3 3 1 4 3 1 1 3
## [39385] 3 2 1 1 1 2 2 4 3 3 3 3 1 2 2 3 2 4 1 1 2 3 3 1 3 4 3 1 4 1 3 3 2 2 3 3
## [39421] 3 3 3 1 2 1 3 1 2 4 3 1 2 3 2 1 3 3 1 1 2 3 3 3 3 1 1 3 2 4 3 1 3 2 2 2
## [39457] 3 1 3 2 2 2 2 1 1 1 3 3 1 3 2 2 2 4 3 1 3 2 4 2 3 1 1 1 3 1 1 3 3 1 1 3
## [39493] 2 3 1 1 2 3 1 1 2 3 2 2 3 2 3 3 3 1 2 3 1 1 1 2 4 2 3 2 4 1 4 1 2 3 2 3
## [39529] 2 3 1 2 2 3 1 3 2 1 3 1 3 2 3 1 3 2 2 2 1 2 2 3 3 1 2 1 1 3 3 3 2 2 4 4
## [39565] 3 3 4 3 2 3 1 2 2 2 4 1 3 3 1 2 3 3 1 2 3 1 4 2 2 1 1 1 3 1 1 1 2 3 3 3
## [39601] 4 3 2 1 1 3 2 3 4 2 1 1 4 3 1 4 4 3 3 3 1 3 3 4 2 2 3 4 3 1 3 2 1 3 3 4
## [39637] 3 1 2 2 1 3 1 4 2 3 2 3 1 2 4 3 3 3 3 2 2 3 2 1 2 1 1 2 2 2 4 1 1 1 2 1
## [39673] 2 3 3 2 1 2 1 3 4 3 2 4 3 2 3 3 3 1 3 3 3 2 3 4 2 1 1 1 4 1 2 2 2 2 3 1
## [39709] 2 2 4 2 2 2 1 1 2 1 3 4 3 2 4 2 3 1 3 1 4 4 2 3 4 1 4 3 1 1 2 1 1 2 3 3
## [39745] 4 2 1 3 3 3 3 1 3 4 4 3 3 3 2 4 1 1 1 1 3 3 2 2 4 3 2 1 1 3 1 3 4 1 2 3
## [39781] 3 3 3 2 3 1 2 2 2 2 1 3 3 2 1 1 3 3 2 4 4 2 3 2 1 3 3 1 3 4 2 3 4 2 1 2
## [39817] 4 3 1 3 3 2 1 1 3 2 3 3 4 1 1 2 1 2 2 1 4 3 3 3 3 3 1 2 2 3 2 1 3 2 1 2
## [39853] 4 1 1 2 3 3 2 4 3 3 3 1 3 1 3 3 4 1 4 3 2 2 1 1 3 2 2 3 2 2 3 3 3 2 1 3
## [39889] 3 3 4 4 3 4 2 3 3 4 3 4 4 3 3 1 1 1 4 2 2 3 2 1 3 4 2 2 3 3 2 4 1 3 2 2
## [39925] 1 2 3 3 3 1 3 3 3 1 2 2 1 1 3 4 2 3 2 2 4 3 1 2 1 2 2 1 1 1 3 3 2 3 2 4
## [39961] 1 3 4 4 3 2 2 3 1 3 4 2 3 1 1 2 3 1 1 1 1 1 1 3 4 2 1 3 2 2 3 2 3 4 2 3
## [39997] 2 4 3 3 3 1 2 3 1 1 3 3 2 3 4 3 2 1 2 1 2 4 3 1 2 1 2 3 2 1 4 3 3 4 2 3
## [40033] 3 2 1 4 2 2 3 3 4 3 2 2 2 1 1 1 1 3 4 3 3 1 2 1 4 1 1 3 1 3 3 1 3 1 3 3
## [40069] 3 2 1 3 2 3 3 1 3 1 3 4 3 3 2 2 4 3 3 2 1 3 4 3 3 1 2 3 2 1 3 1 4 3 1 3
## [40105] 2 2 3 3 3 2 1 2 3 2 1 4 3 1 3 3 4 3 1 4 3 2 1 1 1 4 1 2 2 3 2 2 4 3 1 2
## [40141] 3 1 1 1 3 3 3 3 3 4 1 3 1 3 2 2 3 3 1 2 4 3 1 2 1 3 3 4 2 1 3 2 3 3 3 2
## [40177] 3 1 4 3 3 1 4 2 2 1 2 2 1 1 2 1 3 3 3 2 2 3 3 2 2 1 1 2 3 2 2 2 3 1 1 3
## [40213] 4 2 1 3 3 4 1 3 2 2 3 1 3 4 1 2 4 2 1 2 3 3 1 2 3 3 3 1 1 2 3 2 2 2 3 3
## [40249] 2 3 1 2 3 2 3 3 3 2 3 2 3 1 1 1 1 2 3 4 1 2 3 1 3 1 3 2 3 2 1 3 3 2 3 4
## [40285] 3 3 2 2 2 1 3 2 3 2 2 3 3 2 3 1 1 2 3 3 1 2 2 1 3 1 3 2 4 1 2 3 3 1 4 3
## [40321] 1 1 3 3 1 2 3 2 3 1 1 3 1 3 3 2 1 2 1 2 3 4 3 3 4 3 3 2 3 2 3 3 1 4 3 3
## [40357] 4 3 3 3 1 3 2 3 3 2 4 1 3 1 3 4 4 4 3 4 2 4 2 1 2 1 3 3 4 3 3 4 2 3 3 1
## [40393] 2 3 3 1 2 3 1 3 3 2 2 2 2 2 2 3 3 1 3 3 1 4 2 4 1 3 2 3 4 1 4 1 1 1 3 4
## [40429] 1 1 3 2 3 1 1 1 3 4 2 1 2 3 2 3 2 2 3 3 3 3 1 2 4 2 1 2 4 2 1 2 1 1 3 1
## [40465] 2 3 1 2 1 3 3 1 1 3 1 1 3 1 1 4 3 3 3 2 1 1 2 3 2 3 1 4 1 1 1 2 2 1 3 3
## [40501] 3 3 1 4 4 3 3 4 3 1 4 4 1 2 1 2 1 3 3 3 1 4 2 2 3 2 3 2 4 2 3 3 4 1 2 4
## [40537] 3 2 3 1 1 1 2 1 3 1 2 3 2 1 4 2 1 3 3 3 3 4 1 2 1 2 3 4 2 4 3 2 2 3 1 1
## [40573] 1 3 3 4 4 2 2 3 2 2 3 3 1 3 2 1 2 1 1 2 3 4 3 3 1 1 2 1 3 4 3 2 3 2 1 1
## [40609] 2 3 2 2 3 1 3 1 3 3 3 2 4 3 3 3 1 2 1 3 3 1 3 1 1 3 3 2 1 3 2 2 3 3 1 2
## [40645] 3 3 1 3 2 3 3 3 4 2 3 1 3 1 1 3 2 1 2 2 2 1 2 3 1 3 3 4 1 1 3 3 1 2 2 2
## [40681] 1 2 2 4 2 1 3 3 1 1 3 2 3 3 3 3 3 1 2 3 4 3 2 3 3 3 2 1 1 1 4 4 2 3 4 2
## [40717] 2 3 2 1 3 2 4 2 3 3 3 2 1 1 2 4 2 4 2 3 1 1 3 3 3 3 2 3 4 2 2 2 1 1 3 2
## [40753] 1 3 1 1 3 3 1 1 3 2 1 3 2 1 1 3 1 2 2 2 4 2 1 3 1 3 2 2 3 3 4 3 4 1 1 1
## [40789] 2 3 1 2 3 2 2 4 3 1 3 2 2 4 1 4 4 2 4 3 1 1 3 1 1 2 3 3 1 4 4 3 4 2 1 3
## [40825] 1 3 3 1 2 1 2 1 1 4 2 4 2 2 4 3 1 1 3 3 3 4 2 3 2 1 1 1 3 3 4 3 4 1 4 2
## [40861] 3 2 3 1 1 1 2 1 3 1 4 3 1 3 1 3 2 1 1 3 1 3 3 3 2 2 3 1 3 4 2 3 1 1 2 1
## [40897] 2 1 1 3 4 1 3 3 3 2 1 2 2 3 2 2 3 3 3 2 3 1 4 3 1 1 4 3 2 3 1 2 2 2 3 2
## [40933] 1 4 3 1 4 3 3 3 1 2 3 1 2 3 1 3 2 3 2 1 3 3 3 3 3 2 2 4 3 1 1 3 2 2 1 3
## [40969] 1 1 3 3 1 1 3 3 1 3 3 3 3 2 3 3 1 3 3 3 4 2 3 4 3 4 1 4 3 3 2 3 3 2 4 2
## [41005] 1 3 3 2 2 3 1 4 4 1 1 4 1 2 2 1 2 2 4 2 4 3 2 3 3 3 4 1 3 1 1 2 2 3 1 3
## [41041] 1 3 4 2 3 1 1 3 1 1 2 2 3 4 3 3 1 2 3 1 3 4 2 2 3 3 3 3 1 3 2 1 3 1 4 1
## [41077] 1 1 2 3 1 2 2 1 2 3 4 2 2 2 2 1 4 4 4 3 3 2 3 1 3 2 1 2 3 3 3 3 3 2 1 3
## [41113] 2 3 4 3 1 4 1 3 2 2 3 3 3 3 4 3 2 1 1 3 2 2 1 1 2 3 3 3 3 3 3 1 3 2 3 3
## [41149] 3 3 3 2 2 3 1 2 2 1 3 2 3 1 2 3 3 3 3 3 2 1 3 2 4 3 2 3 4 2 3 3 2 3 2 3
## [41185] 2 4 1 3 4 2 3 3 3 1 1 2 3 3 2 3 3 3 1 1 1 2 2 1 1 2 3 1 1 3 1 3 4 3 2 3
## [41221] 3 2 1 2 2 3 3 2 1 2 2 2 3 1 2 3 1 3 2 2 1 3 3 4 3 1 2 2 1 1 2 2 4 3 3 2
## [41257] 4 2 3 3 3 1 4 1 2 1 2 1 2 2 2 2 1 3 4 4 3 3 2 3 1 2 1 3 3 1 2 1 4 4 3 3
## [41293] 4 3 4 2 1 3 2 1 3 1 1 4 3 3 1 1 2 3 1 2 1 3 3 2 1 3 3 3 4 3 2 3 1 3 3 3
## [41329] 1 1 1 3 3 3 3 2 3 4 3 3 2 3 2 2 1 3 2 1 3 4 3 3 3 2 3 4 2 4 3 1 1 3 3 4
## [41365] 1 3 1 2 1 3 4 3 3 3 3 3 2 1 2 1 3 2 2 2 1 4 3 4 1 3 2 1 3 3 1 4 2 2 1 2
## [41401] 1 2 2 3 3 3 4 1 2 3 3 1 3 4 3 1 1 1 4 4 3 1 2 3 3 2 4 1 3 4 3 2 3 3 3 3
## [41437] 4 3 3 2 3 1 3 3 3 1 1 3 4 2 3 1 1 2 1 3 3 1 3 3 3 3 4 3 1 4 3 3 1 3 1 3
## [41473] 3 2 4 3 1 4 1 2 2 3 3 3 2 1 1 4 3 3 3 4 2 3 2 1 2 3 2 3 4 3 3 2 2 3 2 2
## [41509] 1 2 1 2 2 4 1 3 3 1 1 3 3 3 3 3 1 3 1 2 3 2 4 2 2 3 3 4 3 4 2 2 3 2 2 4
## [41545] 1 2 2 2 4 2 3 2 2 2 3 3 2 4 1 3 3 1 4 3 3 1 2 2 3 1 1 3 2 3 3 3 3 3 1 1
## [41581] 2 3 3 3 3 3 2 3 1 1 2 2 2 3 1 1 1 4 3 2 1 1 1 1 1 2 2 1 2 3 3 1 1 1 4 3
## [41617] 2 2 3 2 1 1 1 3 3 3 2 1 4 3 3 3 3 2 1 2 3 1 2 1 3 3 3 1 1 2 2 3 1 3 3 2
## [41653] 3 3 3 3 1 4 3 4 4 4 2 2 1 3 1 1 4 2 4 4 2 3 1 3 2 3 1 1 3 4 3 3 3 3 3 2
## [41689] 3 1 4 2 1 2 3 3 2 3 3 2 2 1 1 3 4 4 3 4 3 3 1 3 4 3 3 3 1 4 2 3 1 1 2 1
## [41725] 2 1 2 3 3 4 3 3 3 1 3 1 3 2 3 1 2 1 3 2 2 2 3 2 4 2 3 4 3 3 2 2 3 3 3 4
## [41761] 3 3 2 2 3 3 3 1 4 3 2 1 1 1 1 2 3 1 3 1 1 1 3 2 4 1 2 2 3 2 3 1 3 2 4 3
## [41797] 3 3 1 1 1 3 3 1 3 2 3 2 2 1 2 3 3 3 4 2 2 2 4 4 3 1 3 1 3 3 2 2 2 1 3 3
## [41833] 3 2 3 1 2 3 1 3 4 3 1 2 2 4 4 2 2 3 1 3 3 1 4 3 1 3 2 4 3 3 2 3 2 1 1 2
## [41869] 3 2 1 4 2 3 2 4 1 3 1 2 3 2 3 2 3 1 1 3 3 2 2 3 2 1 2 3 2 4 3 2 3 3 3 3
## [41905] 3 2 4 3 2 1 3 1 1 1 3 3 3 3 1 3 1 2 2 2 1 2 4 2 3 1 1 3 2 3 1 1 1 3 4 4
## [41941] 1 1 1 3 3 2 3 2 4 2 2 3 3 2 3 3 1 3 4 2 2 1 1 4 4 3 1 3 2 2 3 1 3 3 3 1
## [41977] 2 1 3 3 3 3 3 3 3 3 1 2 3 2 3 3 4 4 3 3 1 2 1 4 2 4 3 1 2 4 3 3 4 2 4 3
## [42013] 3 2 3 1 1 4 2 3 3 1 4 3 3 2 3 3 3 2 1 2 1 3 3 1 3 2 4 1 4 3 3 4 4 3 4 3
## [42049] 3 1 2 3 3 1 4 3 4 1 3 3 2 3 2 1 2 2 2 2 1 3 3 3 1 4 3 2 2 3 1 3 3 2 1 4
## [42085] 2 3 2 2 2 3 3 3 3 1 3 1 2 3 3 1 1 3 1 3 2 4 2 2 2 3 3 2 2 3 2 2 1 2 3 2
## [42121] 3 3 1 4 3 1 3 2 3 2 4 4 3 2 3 2 2 1 4 2 2 1 1 3 1 1 2 1 3 3 3 3 3 3 3 3
## [42157] 1 2 1 2 3 4 2 4 2 3 2 3 2 1 1 2 2 1 3 3 1 3 4 3 4 3 1 2 2 2 4 3 2 1 3 2
## [42193] 3 3 4 1 1 3 3 2 1 1 4 3 2 2 3 3 3 4 3 1 2 4 4 3 1 3 1 2 1 3 3 3 4 2 3 3
## [42229] 2 2 2 4 2 2 4 4 3 1 4 1 1 2 1 1 4 4 2 1 1 2 1 4 2 2 2 1 2 2 2 2 2 4 2 1
## [42265] 3 3 1 4 2 3 3 1 3 3 2 2 2 1 3 3 2 4 3 4 2 2 3 3 1 2 3 4 3 1 1 3 2 4 3 1
## [42301] 3 1 4 3 4 1 2 3 3 2 3 2 3 4 3 3 3 3 3 3 3 3 2 3 2 2 4 2 2 2 1 3 3 2 3 1
## [42337] 2 1 1 1 4 1 3 1 1 1 1 1 2 2 4 2 3 1 2 4 1 4 1 1 2 3 1 2 3 3 2 1 1 3 3 3
## [42373] 4 1 1 4 2 3 4 1 2 2 4 3 2 2 2 2 2 4 1 4 2 3 3 1 2 2 1 3 3 3 1 3 4 1 3 4
## [42409] 2 1 2 1 4 1 3 1 2 3 1 3 2 2 2 2 3 1 1 2 3 2 1 1 3 3 1 3 4 1 3 4 1 3 4 3
## [42445] 1 1 3 4 1 2 2 1 4 2 2 3 4 3 2 2 1 1 3 1 3 3 1 3 1 3 3 2 2 4 2 4 1 3 1 3
## [42481] 3 3 2 4 3 2 3 2 3 2 1 1 4 4 2 3 4 1 3 2 4 3 2 4 3 1 1 2 2 3 3 1 4 2 1 4
## [42517] 2 2 4 3 4 1 4 1 1 3 2 3 2 3 3 2 3 3 3 3 1 3 3 1 3 1 3 1 2 2 1 3 1 4 4 1
## [42553] 3 3 3 1 2 3 1 2 3 3 3 3 2 3 1 4 3 2 4 3 3 1 1 1 2 3 4 1 3 3 2 2 2 3 4 3
## [42589] 2 2 2 2 4 3 2 3 4 1 3 4 2 4 2 2 1 3 4 2 1 3 1 3 4 1 2 3 4 4 3 3 2 3 2 3
## [42625] 2 4 4 2 4 2 3 1 1 3 1 2 1 1 1 1 3 1 2 3 4 2 1 3 3 3 3 1 2 2 2 1 4 3 1 3
## [42661] 1 1 3 3 1 3 1 2 2 4 4 1 2 3 1 1 3 3 4 3 2 2 2 1 2 2 2 2 3 3 2 4 4 3 2 3
## [42697] 1 1 3 2 1 3 2 4 3 2 4 4 2 1 2 2 1 1 1 3 1 3 1 2 1 1 3 3 2 3 1 1 3 2 2 3
## [42733] 3 3 2 3 4 1 3 1 3 3 4 1 1 1 3 4 3 2 2 3 2 3 4 3 4 3 1 4 3 1 3 1 1 3 3 4
## [42769] 2 2 1 1 2 3 4 1 3 2 3 3 1 2 3 4 3 2 3 3 1 4 3 4 1 1 2 4 3 3 3 1 3 3 1 2
## [42805] 3 3 3 1 1 1 3 2 2 3 3 1 3 2 3 3 3 2 1 1 2 3 2 3 3 1 4 3 4 2 4 4 2 3 3 3
## [42841] 2 3 1 1 4 2 2 1 2 3 3 2 3 1 3 3 2 3 3 2 3 1 3 1 2 3 1 3 2 3 3 2 4 1 3 2
## [42877] 1 2 3 4 2 2 3 2 3 2 3 2 2 2 3 2 2 4 3 2 4 4 2 3 1 3 1 1 2 1 2 1 2 1 2 1
## [42913] 2 2 1 1 3 4 3 3 1 3 2 3 2 3 3 2 4 3 1 2 4 3 2 3 4 2 3 3 3 4 1 1 1 1 1 3
## [42949] 4 1 2 1 4 3 1 2 1 3 3 3 1 3 1 2 1 3 3 1 1 2 3 1 2 2 4 4 2 2 1 1 2 4 3 3
## [42985] 3 1 2 3 1 2 4 3 3 3 3 3 4 3 4 1 3 2 3 2 2 2 1 3 2 2 3 2 1 2 1 2 4 2 4 3
## [43021] 3 1 1 1 3 1 3 2 4 3 2 3 2 3 1 3 3 2 2 1 3 3 3 3 4 3 2 4 2 3 1 1 3 1 2 2
## [43057] 3 1 4 1 2 3 4 3 3 1 2 1 4 3 3 2 3 2 4 4 3 2 2 3 3 3 2 3 3 1 1 1 3 3 2 4
## [43093] 2 4 3 2 3 1 3 4 4 4 1 3 1 1 2 3 3 1 3 4 3 2 1 2 1 3 1 3 3 4 4 3 1 1 2 3
## [43129] 3 3 1 1 3 2 2 2 3 4 3 2 3 2 3 1 2 2 1 4 3 3 1 3 2 1 3 3 3 3 3 3 3 3 1 3
## [43165] 2 2 3 3 4 3 3 3 3 3 3 2 3 2 2 3 2 2 3 2 3 2 3 1 1 2 3 1 3 2 3 1 1 3 4 1
## [43201] 2 1 2 1 3 2 3 1 4 3 3 2 1 3 1 3 3 3 2 1 1 4 3 3 1 2 2 3 3 3 4 3 3 4 3 3
## [43237] 1 3 3 1 1 2 2 3 3 4 3 3 1 1 1 3 3 1 2 3 2 1 2 3 3 1 4 3 1 2 2 1 1 3 3 3
## [43273] 1 1 2 1 2 2 3 1 2 1 3 3 2 2 1 2 3 1 1 2 3 3 1 3 3 3 3 3 3 2 3 3 1 2 1 3
## [43309] 3 4 2 3 1 1 2 4 2 3 2 4 3 3 3 2 3 3 3 4 3 3 1 3 3 2 4 3 2 1 4 2 2 3 3 2
## [43345] 3 4 3 1 2 2 3 4 4 3 3 3 1 2 2 3 3 1 2 3 1 3 3 3 3 1 4 2 4 4 1 2 2 3 3 3
## [43381] 3 3 3 3 3 2 2 3 2 3 2 1 3 2 3 1 1 3 3 3 3 2 4 2 3 1 4 2 1 3 2 3 4 1 4 2
## [43417] 3 1 2 3 3 2 2 3 2 2 3 2 3 3 2 3 3 4 4 1 1 3 3 3 3 2 1 1 3 2 3 3 3 1 2 2
## [43453] 4 2 1 2 1 2 4 1 4 1 3 2 1 2 3 1 3 2 2 2 3 2 1 1 4 2 4 3 1 2 3 2 2 2 1 2
## [43489] 4 4 3 2 3 1 4 3 3 2 3 2 3 3 1 3 2 1 2 4 2 1 2 3 4 4 1 3 3 4 2 2 3 3 2 3
## [43525] 3 2 3 4 1 3 1 3 1 3 4 3 1 1 3 2 3 3 1 2 4 3 3 4 2 2 2 1 3 3 3 1 3 3 3 3
## [43561] 1 3 2 2 3 4 3 1 3 1 3 1 3 2 3 2 2 3 3 1 4 1 4 2 3 1 1 1 2 3 4 3 3 3 1 3
## [43597] 1 4 2 3 2 3 3 1 2 1 3 3 2 2 3 2 2 4 3 3 1 3 2 2 4 3 3 1 4 4 4 2 4 3 2 2
## [43633] 3 1 1 2 3 4 3 2 4 4 3 2 3 2 4 4 2 1 4 2 3 3 2 2 1 3 3 4 2 3 3 3 3 2 3 1
## [43669] 3 3 2 1 2 2 2 1 3 1 3 3 1 1 1 2 3 4 2 4 1 1 2 3 3 4 3 1 4 3 2 4 1 3 4 1
## [43705] 4 2 2 1 2 2 3 2 2 1 3 4 2 3 1 4 3 1 4 3 2 4 2 1 2 4 1 3 1 1 3 3 3 3 3 3
## [43741] 1 1 1 1 2 4 2 2 3 3 3 3 1 4 1 1 2 1 3 4 3 1 2 2 4 4 4 3 3 3 3 3 1 4 1 1
## [43777] 4 1 3 4 3 1 4 3 3 1 3 4 1 3 4 3 2 2 1 4 2 4 2 4 3 4 2 2 1 3 2 3 2 2 1 3
## [43813] 1 3 3 2 1 3 2 3 2 3 1 2 1 1 1 4 1 4 2 3 3 3 2 1 2 4 3 1 4 3 1 1 1 4 3 2
## [43849] 1 2 2 2 4 3 2 3 4 3 1 2 2 2 1 2 2 3 2 2 3 1 1 3 2 2 2 3 3 3 2 3 4 1 2 2
## [43885] 4 2 3 1 3 1 1 1 1 1 4 1 2 1 1 4 1 2 1 1 3 1 3 3 1 3 3 2 3 1 2 1 2 3 3 4
## [43921] 1 3 1 3 2 3 4 3 4 2 2 1 1 2 3 2 3 2 1 2 2 3 4 2 2 2 2 3 3 2 4 3 2 4 4 1
## [43957] 1 3 2 3 2 4 1 3 3 2 1 1 4 1 1 2 2 2 1 2 2 3 1 3 4 3 3 1 4 1 4 4 3 3 2 4
## [43993] 3 3 1 4 3 3 4 2 3 3 2 1 3 4 3 2 1 1 1 3 3 2 3 1 3 3 3 2 2 4 3 3 3 4 4 1
## [44029] 1 1 2 2 3 2 4 1 3 3 1 3 2 4 4 1 2 1 2 2 2 1 1 1 4 4 3 1 3 3 2 2 2 1 2 3
## [44065] 2 2 1 2 1 2 3 1 4 3 1 3 4 2 1 2 2 2 4 3 2 1 4 4 1 4 4 2 2 4 3 2 1 4 2 3
## [44101] 2 3 2 4 2 1 1 3 1 4 1 2 3 4 3 2 3 3 1 1 3 3 2 3 3 2 3 2 2 3 1 3 3 4 2 1
## [44137] 1 2 3 2 3 1 1 3 4 4 2 3 1 1 3 1 2 3 3 3 3 1 3 2 1 3 3 3 4 3 1 4 1 3 1 2
## [44173] 3 4 3 3 3 2 1 4 3 1 3 1 2 3 1 1 3 3 3 2 3 4 1 2 3 3 1 4 3 1 1 3 3 3 1 1
## [44209] 3 1 3 1 1 4 3 2 3 4 1 4 1 1 2 3 1 3 1 2 1 4 1 1 1 1 1 1 3 1 2 2 3 1 1 3
## [44245] 1 3 1 3 3 2 1 3 3 1 1 1 3 2 1 3 3 2 2 2 2 2 3 3 4 1 4 3 2 1 1 2 3 1 3 4
## [44281] 3 4 1 3 4 1 1 3 4 3 3 3 3 2 2 1 2 3 2 2 3 3 1 3 3 3 1 2 4 3 2 1 3 3 4 1
## [44317] 1 3 3 3 3 3 3 3 2 3 2 2 2 1 4 1 3 4 1 2 4 3 3 1 1 4 2 2 3 4 2 3 2 2 1 3
## [44353] 3 2 2 4 4 1 4 3 3 3 3 2 2 3 3 1 1 2 3 1 2 3 3 3 1 2 3 2 3 3 3 3 1 3 1 2
## [44389] 2 3 2 1 4 4 3 2 2 2 1 2 3 1 3 2 1 2 4 3 2 3 4 1 3 3 3 2 2 3 4 4 1 1 3 4
## [44425] 3 2 3 2 3 4 2 3 3 4 3 3 1 3 1 4 3 1 3 3 2 3 3 2 1 3 4 2 3 3 2 3 1 3 1 3
## [44461] 2 2 3 2 3 2 3 2 1 4 3 2 2 1 3 3 3 3 2 3 4 4 2 2 4 2 3 1 3 1 4 2 2 1 3 4
## [44497] 3 2 2 2 1 3 1 3 2 2 4 1 3 2 1 4 3 4 3 4 3 4 4 3 3 1 3 2 2 1 3 3 2 4 4 1
## [44533] 3 1 1 1 2 1 1 2 3 3 4 3 1 3 2 1 3 2 1 3 3 2 1 3 3 3 3 2 1 2 2 3 1 2 2 2
## [44569] 2 2 4 1 2 1 2 2 4 4 2 1 3 3 3 3 3 4 2 3 3 2 3 1 3 2 3 2 2 1 4 3 4 2 4 1
## [44605] 4 1 1 4 2 2 3 2 3 3 3 3 3 2 1 1 2 2 1 4 1 1 3 1 1 1 1 3 3 4 4 3 2 3 3 3
## [44641] 2 1 3 1 3 4 4 2 2 2 3 1 4 3 3 2 3 1 3 3 3 1 4 3 2 1 2 2 2 3 3 1 3 3 1 3
## [44677] 3 3 3 2 3 3 1 4 3 3 3 3 3 3 1 2 4 4 3 1 3 1 3 4 3 1 3 4 1 3 3 3 4 3 4 3
## [44713] 4 3 2 2 2 1 2 3 2 2 2 3 2 3 1 2 2 2 4 2 2 3 4 3 1 2 3 2 4 3 2 4 3 4 3 4
## [44749] 3 2 3 3 2 2 3 1 2 4 2 3 3 4 2 4 3 2 1 3 3 2 4 1 3 2 1 3 3 2 3 1 4 3 2 2
## [44785] 1 1 4 3 3 2 1 3 3 3 2 1 1 3 2 3 3 1 2 2 3 1 3 3 2 3 2 3 3 3 3 2 3 3 3 2
## [44821] 3 1 1 4 3 1 4 3 1 3 1 3 2 2 3 3 4 1 3 2 3 1 1 3 3 4 2 2 3 1 1 4 2 2 4 1
## [44857] 4 2 4 1 3 2 3 2 2 4 3 3 3 4 3 3 1 4 3 4 4 2 2 3 3 2 2 3 1 3 4 3 1 3 2 2
## [44893] 1 1 1 3 3 1 3 3 3 4 2 1 1 3 3 1 2 3 1 1 2 2 4 3 3 1 4 1 3 3 1 2 3 3 1 3
## [44929] 2 4 2 2 1 3 1 2 3 1 3 3 3 4 1 3 4 1 3 1 1 3 1 3 2 1 3 1 4 1 4 3 1 1 4 4
## [44965] 4 2 1 4 1 4 3 4 1 4 2 1 2 2 3 1 4 1 1 3 3 2 1 1 2 1 3 4 3 1 3 2 3 1 1 2
## [45001] 3 1 3 3 1 2 3 3 3 3 1 4 3 4 2 2 3 3 4 3 4 2 3 3 3 2 3 3 2 1 2 1 1 3 2 4
## [45037] 1 2 1 1 2 3 1 1 3 3 2 3 1 1 3 3 3 1 1 3 1 1 2 1 3 1 1 1 3 1 3 1 3 3 3 1
## [45073] 2 1 3 3 3 1 4 3 4 3 2 2 2 1 3 3 4 2 2 1 4 3 3 3 4 1 1 2 2 1 1 1 2 3 1 3
## [45109] 3 4 3 1 2 3 3 2 3 2 2 3 1 4 1 3 4 3 3 3 1 3 1 4 2 1 2 3 3 2 3 1 3 4 1 2
## [45145] 2 3 3 3 1 3 1 3 2 1 3 2 2 3 1 4 4 1 1 1 3 2 1 3 2 3 4 1 3 4 3 1 4 1 1 1
## [45181] 1 1 1 3 3 1 3 1 2 3 4 1 1 3 2 3 1 3 2 2 1 3 1 3 4 3 3 1 2 4 2 1 1 4 2 3
## [45217] 2 4 3 2 3 2 2 3 1 1 3 2 3 2 3 1 1 3 2 2 3 3 3 2 2 2 3 4 3 3 3 1 3 4 1 3
## [45253] 3 4 4 2 3 1 2 3 3 3 3 1 3 2 3 3 2 2 2 2 1 3 3 3 2 3 2 4 3 3 3 4 2 1 2 3
## [45289] 1 2 3 3 2 4 2 2 3 1 1 4 3 3 4 3 2 4 2 2 3 1 2 2 3 1 2 3 1 4 2 2 1 1 2 2
## [45325] 3 1 3 1 2 3 3 1 2 3 3 2 2 3 2 3 3 3 3 2 2 3 4 4 2 1 3 1 3 4 2 2 4 1 1 4
## [45361] 4 3 2 3 4 1 3 3 1 3 3 1 3 3 1 3 3 2 1 2 2 3 1 1 2 4 3 1 1 4 2 1 4 3 3 1
## [45397] 2 4 1 4 1 2 3 3 2 1 4 2 3 3 3 3 2 2 3 3 3 4 3 3 3 2 2 1 3 2 3 2 4 3 3 1
## [45433] 1 3 2 4 1 1 2 3 1 3 3 1 4 3 4 3 3 2 2 3 3 4 1 3 4 3 4 2 1 2 4 2 2 1 4 4
## [45469] 4 3 2 1 1 2 4 3 1 2 1 4 2 4 1 2 2 1 4 2 1 1 2 3 2 3 4 1 3 1 3 3 3 3 1 1
## [45505] 4 3 2 1 2 3 2 2 3 2 2 2 3 3 3 2 3 3 2 1 3 2 3 2 2 2 3 2 4 1 1 2 1 1 2 3
## [45541] 3 3 3 3 3 4 1 1 3 3 3 2 2 2 3 3 1 3 3 2 1 2 1 2 2 1 3 3 1 3 4 2 3 3 3 4
## [45577] 4 2 1 2 3 2 3 3 1 3 3 2 2 3 1 4 4 2 2 3 3 2 1 2 2 4 3 4 2 3 3 3 2 1 1 4
## [45613] 1 3 3 2 2 2 3 3 2 2 4 3 1 1 3 3 3 4 2 3 4 3 3 3 2 4 4 3 3 1 4 2 3 3 3 2
## [45649] 2 4 4 2 1 2 3 3 1 3 3 3 4 3 3 2 2 4 3 2 4 4 2 3 3 4 2 3 1 2 2 3 2 1 4 1
## [45685] 2 1 2 1 4 2 4 2 3 2 1 1 3 3 2 3 3 3 2 1 3 3 4 2 2 3 2 1 4 2 1 3 2 3 2 1
## [45721] 3 2 3 4 2 3 4 2 1 2 3 3 2 3 1 1 4 3 1 4 3 2 2 3 1 3 4 2 2 3 3 1 4 2 1 1
## [45757] 1 3 1 1 3 3 1 4 3 3 2 2 1 3 3 2 3 1 4 4 2 3 3 3 1 3 3 2 1 1 1 1 1 2 3 3
## [45793] 1 1 3 3 3 3 4 1 3 4 3 1 3 3 3 2 3 2 1 3 3 1 4 3 1 3 4 1 2 1 2 4 2 3 1 3
## [45829] 2 2 2 1 3 1 2 3 4 1 1 2 4 3 1 1 1 4 1 2 3 2 4 2 3 2 2 1 3 1 2 1 2 3 3 1
## [45865] 2 2 1 1 1 3 3 3 2 3 2 3 2 1 3 4 1 3 1 4 2 3 2 3 2 4 3 3 4 3 2 3 3 2 2 2
## [45901] 2 2 2 3 3 2 1 4 1 2 3 3 3 2 3 3 2 3 1 2 1 1 3 1 2 1 2 3 3 1 3 1 2 2 2 3
## [45937] 2 3 1 1 4 2 1 3 3 1 2 3 2 3 2 4 3 2 1 3 1 1 4 3 4 3 4 2 2 3 4 3 3 4 1 1
## [45973] 4 2 1 2 3 1 3 2 1 3 1 1 2 3 1 1 2 3 3 3 3 3 1 3 3 3 3 4 4 3 2 3 3 2 2 3
## [46009] 2 2 1 1 3 3 1 1 2 3 3 3 2 3 2 3 3 4 1 1 3 1 3 2 1 4 3 1 3 3 1 2 3 4 3 4
## [46045] 3 3 1 3 4 3 1 1 2 1 3 1 2 3 1 2 3 2 2 3 4 1 1 2 2 4 3 4 3 3 1 3 3 1 4 3
## [46081] 2 2 3 1 4 3 3 1 2 1 3 3 1 2 2 2 3 1 3 1 3 1 3 1 1 3 1 1 2 3 3 3 3 3 1 3
## [46117] 1 2 1 2 3 2 3 3 1 4 4 2 3 2 3 1 2 3 3 1 3 3 2 2 2 1 2 2 3 3 3 4 3 3 1 2
## [46153] 1 3 1 3 3 3 3 2 3 3 3 4 3 2 3 1 2 1 3 3 1 2 2 1 2 3 3 1 3 1 3 3 2 2 3 3
## [46189] 2 3 1 1 3 1 1 3 1 1 1 2 3 2 2 3 3 1 1 4 1 1 3 2 1 2 1 2 2 1 3 2 2 2 1 1
## [46225] 1 3 3 2 3 2 3 1 1 1 2 1 2 3 3 2 2 2 3 1 2 1 4 3 3 3 2 3 3 3 3 1 4 1 4 2
## [46261] 2 4 3 4 3 1 2 4 2 3 1 1 4 2 1 1 3 1 2 4 1 3 3 3 3 1 1 3 2 3 2 2 1 1 2 3
## [46297] 3 3 1 4 1 3 3 1 1 3 1 2 3 4 3 1 3 3 2 3 1 2 2 3 1 3 1 4 3 2 3 2 3 2 4 3
## [46333] 1 1 3 2 2 2 3 3 2 3 1 2 3 3 1 4 1 2 4 1 2 2 2 3 3 4 1 3 1 4 1 1 1 3 3 1
## [46369] 3 3 4 1 1 4 3 1 2 2 4 3 3 2 2 1 4 3 4 3 2 3 2 1 3 3 2 4 3 2 4 1 4 1 2 2
## [46405] 3 1 3 1 1 1 3 3 4 2 2 2 2 3 1 3 3 3 4 3 1 1 4 4 1 1 1 2 1 2 2 2 3 2 2 3
## [46441] 4 2 3 2 2 3 4 3 3 2 4 2 3 2 1 3 2 1 1 2 2 1 3 3 3 4 2 1 1 3 2 3 4 2 3 2
## [46477] 1 1 3 3 2 3 3 3 3 4 1 2 2 3 1 2 1 2 4 2 3 1 2 1 3 4 4 3 2 2 3 1 3 3 3 1
## [46513] 1 1 1 3 3 2 3 3 4 1 4 2 4 1 3 1 2 4 1 3 3 2 2 4 2 3 2 2 3 3 2 3 3 4 3 1
## [46549] 4 1 3 3 2 2 3 1 3 2 2 4 3 4 1 1 2 3 2 2 1 3 3 3 3 3 3 3 2 2 2 1 3 2 3 2
## [46585] 3 3 1 3 1 3 2 1 2 2 3 3 4 2 3 3 3 1 3 2 3 3 4 2 4 2 3 2 3 1 3 3 2 3 2 3
## [46621] 3 3 1 4 4 3 2 3 2 2 3 3 2 4 4 3 3 2 1 3 3 3 1 3 3 4 1 3 2 2 3 3 2 3 1 2
## [46657] 1 3 3 3 4 1 3 1 3 3 1 3 1 2 3 1 3 3 4 2 4 4 3 2 4 3 3 1 2 2 3 1 3 2 3 1
## [46693] 2 3 3 4 1 2 4 4 2 3 3 2 3 1 1 3 3 4 2 4 1 1 2 1 1 2 3 2 2 4 3 2 2 4 2 3
## [46729] 1 3 2 1 3 2 2 2 2 2 3 3 3 1 3 3 3 2 1 3 3 1 2 3 2 1 3 3 3 2 3 3 1 1 3 4
## [46765] 3 4 2 3 3 2 3 3 2 3 3 2 2 2 1 3 3 4 1 3 3 1 3 3 2 1 1 3 2 3 1 1 1 3 3 4
## [46801] 1 3 1 2 2 2 3 2 3 3 1 3 1 2 2 1 1 4 2 4 3 1 3 4 4 1 1 3 3 1 2 4 1 2 3 2
## [46837] 1 3 4 2 3 1 2 2 1 1 4 1 1 4 1 2 3 2 3 2 2 2 3 2 2 3 3 3 4 2 1 3 4 3 3 4
## [46873] 2 3 1 1 2 2 3 2 4 1 1 2 1 1 4 3 1 1 2 3 2 1 1 1 3 2 1 4 2 4 4 3 1 1 2 1
## [46909] 3 3 2 2 3 3 2 3 1 4 1 1 3 2 2 3 2 1 1 3 2 3 3 1 3 4 1 3 1 3 4 1 1 4 2 3
## [46945] 3 1 3 2 2 2 3 3 4 2 3 4 3 2 3 3 3 4 3 4 4 3 1 3 2 1 3 3 2 2 2 3 3 1 2 3
## [46981] 3 1 3 2 2 3 4 2 3 1 2 3 2 2 3 1 3 1 3 2 2 1 2 1 3 2 3 3 2 3 1 4 4 2 1 3
## [47017] 4 1 3 1 2 4 3 2 3 2 1 1 4 3 1 1 3 1 4 4 1 3 1 3 3 4 2 2 3 3 3 1 1 2 2 3
## [47053] 3 4 2 3 3 1 3 3 3 4 1 4 3 2 1 1 1 1 2 3 3 3 1 2 1 4 2 1 3 2 1 1 1 2 4 1
## [47089] 1 4 2 3 2 4 4 2 3 3 1 1 4 4 4 2 3 1 1 2 3 2 3 3 1 1 2 1 3 1 1 4 4 1 1 4
## [47125] 3 3 1 1 4 3 2 3 3 4 1 2 2 3 1 1 2 4 2 3 3 1 2 2 4 3 4 3 2 3 1 1 3 1 4 2
## [47161] 2 2 1 3 3 4 1 1 3 1 1 1 2 2 1 2 3 1 3 1 3 3 3 3 3 3 1 4 4 3 1 1 3 1 1 3
## [47197] 1 1 3 1 3 2 3 1 4 3 3 2 1 2 3 2 3 3 2 2 1 1 4 1 4 2 3 3 3 2 2 1 3 3 1 2
## [47233] 2 2 3 2 3 2 2 4 3 1 1 2 1 3 2 1 3 3 3 3 3 3 3 3 3 2 1 1 3 3 2 3 1 3 4 3
## [47269] 1 3 1 2 3 1 2 2 1 1 2 2 1 3 1 4 3 2 3 3 4 2 3 1 2 3 4 2 2 3 3 3 1 3 1 2
## [47305] 1 3 3 3 3 3 3 3 1 3 4 3 3 1 2 2 2 3 3 2 1 4 2 3 3 4 1 3 2 2 3 4 1 3 3 3
## [47341] 2 1 3 2 4 1 1 2 3 2 1 3 3 2 3 4 3 4 3 3 3 3 1 3 3 1 3 4 3 2 3 2 1 1 4 2
## [47377] 2 2 2 1 3 2 3 2 2 1 3 4 3 3 2 2 3 3 3 4 3 1 1 4 3 2 2 3 1 3 2 3 3 3 2 4
## [47413] 3 1 3 3 1 2 3 4 1 2 2 2 1 3 3 4 1 2 3 3 2 3 4 3 2 2 1 1 2 3 2 2 2 1 2 1
## [47449] 3 2 3 4 4 3 2 3 4 3 4 2 4 4 1 1 2 2 1 2 2 2 3 1 4 2 1 2 2 2 2 2 2 3 3 3
## [47485] 3 3 1 2 1 2 2 3 4 4 4 4 3 1 4 2 3 3 4 1 2 3 3 2 2 1 1 3 3 2 1 3 3 4 1 3
## [47521] 2 4 2 2 4 3 2 2 1 3 3 4 1 3 2 1 2 3 2 1 4 3 1 3 2 3 4 2 2 2 3 3 1 3 3 3
## [47557] 3 3 3 3 2 3 3 3 1 2 2 3 3 2 1 3 3 3 3 3 3 3 3 2 3 3 2 1 4 1 2 2 2 4 1 3
## [47593] 4 2 3 2 3 3 4 1 2 3 2 2 1 3 1 2 3 2 2 2 3 3 3 2 3 3 2 1 1 2 1 4 2 2 3 2
## [47629] 3 3 4 1 2 1 1 2 3 1 4 1 3 2 3 3 3 4 3 1 4 3 2 3 2 4 3 3 3 2 2 3 3 3 3 4
## [47665] 3 3 3 1 3 3 3 3 1 3 4 2 3 4 2 2 1 2 2 3 1 3 3 1 2 3 4 1 3 3 1 3 1 1 2 2
## [47701] 2 1 3 3 3 1 2 2 3 1 1 3 3 4 3 3 3 4 1 3 3 3 2 3 2 3 2 3 1 2 4 3 4 2 2 3
## [47737] 3 1 3 1 2 3 3 1 2 1 3 1 3 3 3 1 3 4 1 2 2 2 2 3 3 1 2 1 1 3 4 2 2 3 4 3
## [47773] 1 2 1 3 3 3 2 4 1 1 2 3 3 2 2 2 3 2 3 1 1 3 4 3 3 4 2 4 2 2 4 4 3 1 3 3
## [47809] 1 3 2 3 3 3 1 3 3 1 1 3 2 1 1 1 2 1 4 2 2 2 3 3 2 3 1 2 1 3 3 2 3 2 1 3
## [47845] 2 1 3 3 3 4 2 3 1 3 2 1 3 4 3 1 3 2 3 4 3 3 2 2 4 4 2 1 3 1 1 3 3 3 1 2
## [47881] 4 3 1 4 3 3 2 1 2 1 3 3 3 4 2 2 4 2 1 2 2 3 4 3 3 3 3 4 3 4 3 2 3 2 2 4
## [47917] 1 3 3 3 2 1 1 2 3 1 3 3 3 1 2 4 3 3 2 3 2 3 1 3 1 1 4 1 2 3 3 3 1 2 1 4
## [47953] 2 2 2 2 1 2 4 3 4 1 3 1 1 3 2 2 4 1 4 3 4 1 3 3 2 2 2 2 3 1 3 3 2 2 3 1
## [47989] 3 3 2 3 2 4 1 3 4 4 2 4 1 3 1 1 1 4 3 3 1 1 2 2 4 2 3 1 1 2 3 2 3 3 1 2
## [48025] 4 1 4 3 3 2 3 1 1 2 1 3 2 4 1 2 1 3 3 1 1 4 2 1 2 3 3 1 2 3 3 2 3 2 3 3
## [48061] 1 3 1 2 4 1 4 3 2 1 2 4 2 4 2 1 2 4 1 2 2 4 2 2 1 3 3 3 2 2 2 3 2 4 3 1
## [48097] 2 3 2 2 3 1 1 1 1 1 3 1 1 3 2 4 4 2 3 3 3 1 2 3 4 1 3 3 1 4 2 3 3 3 2 2
## [48133] 2 1 3 1 1 4 2 1 4 2 2 3 1 3 3 3 2 4 2 3 1 3 2 1 2 1 3 3 2 2 3 4 4 2 3 3
## [48169] 2 2 2 3 4 2 3 4 1 1 1 2 2 1 3 2 3 2 3 3 1 2 2 2 2 1 3 1 3 2 2 1 1 2 3 3
## [48205] 3 1 3 3 2 1 3 3 1 1 2 1 3 4 2 1 3 1 3 1 3 3 2 2 4 2 2 2 4 3 4 3 2 3 3 2
## [48241] 4 4 3 1 2 3 1 4 1 4 4 4 3 3 3 3 2 3 3 3 3 4 3 1 2 2 4 3 1 1 2 1 2 2 3 3
## [48277] 4 2 3 1 3 2 1 1 3 2 1 2 4 3 2 3 4 4 2 4 3 2 2 1 1 4 1 3 3 3 1 2 4 2 2 4
## [48313] 3 4 1 2 1 3 3 4 4 3 3 3 2 1 2 1 2 3 3 2 4 3 2 1 3 3 2 1 2 1 1 2 2 4 3 1
## [48349] 3 2 2 2 3 1 2 2 3 3 4 1 2 1 2 2 3 3 1 2 2 1 3 1 2 3 3 4 2 1 3 2 1 3 2 4
## [48385] 1 4 2 1 3 2 1 2 3 2 1 2 3 1 3 1 3 1 1 3 1 1 3 1 4 2 3 3 3 1 2 3 2 3 4 3
## [48421] 3 4 1 2 3 2 3 4 4 3 1 1 4 4 4 1 3 1 2 1 3 1 2 4 3 3 2 4 3 2 2 3 3 4 2 1
## [48457] 3 1 2 2 2 2 3 4 4 3 4 3 1 3 2 3 3 3 1 3 4 2 2 3 3 3 3 1 3 3 2 1 2 1 2 1
## [48493] 3 3 3 3 3 1 3 3 3 1 2 4 2 2 2 3 3 3 2 3 4 3 2 2 2 4 1 2 4 3 1 2 1 1 1 1
## [48529] 3 4 3 1 2 2 3 3 3 3 2 2 3 2 3 2 3 2 3 1 2 1 2 2 3 1 1 1 3 1 3 3 3 3 3 2
## [48565] 3 1 2 2 1 3 1 1 1 2 1 2 4 4 1 3 1 4 2 3 1 1 2 4 2 3 4 3 3 2 3 3 3 3 2 3
## [48601] 2 4 2 1 2 1 2 2 1 4 2 2 4 2 3 2 4 1 3 2 3 2 3 4 3 4 3 1 3 3 1 2 3 3 4 4
## [48637] 4 1 1 2 3 3 2 3 3 1 2 1 3 3 2 1 2 2 3 3 3 2 2 1 4 1 3 3 4 4 1 3 3 3 1 2
## [48673] 2 3 2 1 3 1 4 3 2 3 1 2 4 1 1 1 3 3 1 4 2 4 4 1 2 3 1 4 3 2 3 3 4 2 1 3
## [48709] 1 1 1 3 4 1 3 3 1 3 3 4 2 2 3 4 1 4 1 1 2 1 2 2 3 1 3 1 2 2 1 3 3 3 2 1
## [48745] 2 4 1 4 3 4 4 3 2 1 3 3 2 2 1 3 3 2 2 1 2 2 1 2 2 3 4 1 1 2 3 1 3 3 4 1
## [48781] 3 3 2 1 2 3 1 4 2 4 4 2 3 2 1 2 2 1 3 2 2 3 1 3 2 3 2 3 1 4 2 3 1 1 2 4
## [48817] 2 2 2 1 4 3 1 1 2 2 3 3 3 2 2 3 1 1 2 4 3 4 4 4 3 1 3 3 4 3 2 3 3 4 4 3
## [48853] 2 4 2 1 1 1 3 2 1 3 3 3 2 1 3 3 2 3 2 2 3 3 2 1 4 3 2 4 4 3 3 3 4 4 3 3
## [48889] 3 1 4 1 3 1 2 3 3 3 3 2 2 3 2 3 2 3 1 1 3 2 3 3 2 2 3 1 2 2 3 2 3 3 1 3
## [48925] 2 3 2 4 4 3 3 2 1 1 4 2 4 1 1 3 3 3 2 1 3 3 1 2 3 3 4 2 3 1 2 1 3 1 2 2
## [48961] 2 1 3 2 1 1 4 2 4 3 1 2 4 1 3 3 2 1 2 3 1 1 1 4 3 3 1 2 1 3 1 1 3 3 1 3
## [48997] 3 4 1 2 4 3 3 3 3 3 3 4 3 1 3 3 1 3 3 3 3 1 2 2 3 2 1 3 4 3 3 2 2 1 4 1
## [49033] 3 1 4 2 1 1 3 4 4 4 3 1 2 2 2 3 2 2 1 2 2 1 2 2 2 2 3 4 3 1 3 3 3 4 2 3
## [49069] 1 3 3 3 3 1 4 3 1 1 4 2 1 1 4 3 2 4 1 1 2 2 2 3 3 2 3 3 3 1 3 2 1 2 3 3
## [49105] 3 1 2 4 3 2 2 2 3 1 3 1 3 3 1 1 3 2 4 3 4 3 1 4 2 3 3 4 3 4 3 2 4 2 4 3
## [49141] 2 1 1 1 4 4 3 4 2 1 2 4 1 3 4 3 2 2 3 2 2 1 1 3 3 3 2 3 3 3 3 3 3 3 3 4
## [49177] 2 4 2 1 3 3 1 2 1 3 3 3 3 4 2 3 1 3 1 1 1 3 1 3 3 2 1 3 3 1 1 1 3 3 1 3
## [49213] 2 3 3 3 1 2 3 3 4 3 3 1 2 4 2 1 2 4 1 4 1 3 1 3 2 1 3 2 1 2 2 1 2 2 4 3
## [49249] 2 2 3 2 1 4 3 3 2 3 3 2 3 3 2 4 1 1 1 2 2 1 4 2 2 2 2 3 2 3 3 3 2 2 3 2
## [49285] 1 1 1 4 4 3 3 1 3 3 3 2 3 1 4 1 4 1 3 4 3 1 2 1 1 3 3 2 3 1 3 3 3 2 2 4
## [49321] 3 3 2 1 2 1 3 1 3 2 4 2 1 2 2 3 1 3 3 3 3 4 2 3 4 3 3 3 2 3 4 3 4 3 2 4
## [49357] 2 3 1 2 2 3 3 2 1 2 3 2 2 1 3 4 2 4 4 2 1 4 2 2 2 2 1 1 1 2 2 3 1 1 1 4
## [49393] 1 1 3 2 2 1 3 4 2 3 1 3 3 2 1 3 3 1 2 1 4 1 3 2 3 3 2 1 4 4 2 2 1 2 1 3
## [49429] 2 3 1 1 1 2 1 3 4 1 1 3 2 2 3 4 4 1 4 1 3 1 3 1 1 3 1 1 2 2 2 2 3 2 2 1
## [49465] 4 3 3 4 3 2 1 1 1 1 2 1 1 3 1 1 3 4 4 2 2 2 1 3 3 4 2 2 1 4 4 3 2 2 3 2
## [49501] 3 3 3 1 3 4 1 2 4 3 2 1 1 3 4 1 3 4 1 2 3 1 3 1 3 3 1 3 3 3 3 2 1 1 1 3
## [49537] 3 3 3 2 3 3 2 3 4 2 2 1 4 2 3 1 3 2 1 3 2 1 2 3 2 1 1 2 3 3 1 4 1 3 1 3
## [49573] 3 3 2 3 2 2 2 3 4 3 1 3 3 2 2 3 2 3 3 4 3 1 3 1 3 1 2 3 2 3 4 3 3 4 4 3
## [49609] 2 1 3 3 3 3 4 2 3 4 3 4 1 1 1 2 1 3 2 3 3 3 3 3 3 2 3 1 4 1 4 3 3 3 2 3
## [49645] 3 3 1 3 1 4 3 3 3 2 3 2 1 2 3 3 4 2 3 1 3 1 2 3 1 3 3 3 1 4 3 3 3 3 3 1
## [49681] 1 4 2 2 3 3 3 3 3 2 3 2 3 3 2 1 3 4 2 1 3 2 3 4 3 3 2 2 3 1 2 3 4 3 1 1
## [49717] 4 3 4 3 2 3 2 3 2 3 1 1 1 2 2 2 1 3 1 1 2 2 2 2 3 1 4 3 2 3 2 3 2 2 2 3
## [49753] 2 2 2 1 3 3 2 2 3 2 1 3 3 3 2 2 3 3 3 1 3 3 2 1 4 2 1 3 2 3 3 1 3 2 2 1
## [49789] 2 3 1 3 1 4 1 2 1 2 4 1 3 3 3 3 2 3 2 1 2 1 1 2 2 2 1 3 2 3 3 2 1 3 4 1
## [49825] 2 1 3 1 3 1 3 3 3 4 1 2 2 2 3 1 3 2 1 1 3 1 3 1 3 4 3 3 2 3 3 3 4 1 1 1
## [49861] 2 1 1 3 2 3 3 2 1 1 4 3 3 4 3 2 3 2 4 2 4 2 3 4 1 4 4 4 2 3 3 3 1 3 3 2
## [49897] 1 3 3 3 2 1 1 3 3 3 1 2 2 3 4 2 3 1 2 1 4 2 3 2 1 3 2 4 2 1 1 4 3 2 3 2
## [49933] 2 1 1 3 1 2 2 1 1 2 1 4 3 2 3 4 3 3 1 1 1 3 3 3 1 4 2 3 3 1 3 1 3 1 4 3
## [49969] 2 1 1 3 3 1 2 1 3 1 3 1 3 2 2 3 3 3 1 3 1 2 1 1 1 1 3 3 2 2 2 1 3 4 2 2
## [50005] 1 3 3 1 4 2 1 3 3 2 4 1 4 3 2 2 4 1 3 3 1 3 1 3 2 2 2 3 3 2 2 4 3 3 3 2
## [50041] 1 2 3 4 2 1 3 2 3 1 3 2 1 3 3 3 2 3 3 4 2 2 4 1 2 4 3 3 2 1 1 3 3 3 2 1
## [50077] 1 2 2 3 1 1 2 3 2 1 2 3 2 3 1 2 2 3 3 1 1 1 1 3 1 3 3 3 3 2 3 1 2 4 1 4
## [50113] 1 3 3 1 3 3 3 4 3 1 2 2 2 3 4 4 2 4 2 2 2 2 1 4 2 3 1 4 3 1 2 1 1 1 4 3
## [50149] 1 3 2 1 1 2 3 4 1 1 1 3 2 3 1 3 3 3 2 4 3 2 1 4 4 4 1 1 2 2 3 1 2 3 3 3
## [50185] 1 2 4 2 3 2 1 3 3 2 2 2 2 1 1 2 2 2 2 1 2 1 3 2 2 1 3 3 3 3 3 2 4 4 2 3
## [50221] 4 1 1 2 2 1 2 3 1 1 2 2 3 1 3 1 4 1 3 2 3 2 3 1 4 1 2 2 3 4 1 1 4 2 1 2
## [50257] 3 2 2 1 3 3 3 3 3 3 3 3 2 2 3 1 1 2 1 3 2 2 3 3 3 4 2 3 3 3 2 1 2 3 3 4
## [50293] 4 1 4 1 4 3 3 3 2 1 2 3 3 3 1 2 2 3 3 3 1 3 2 1 4 4 3 2 3 4 2 1 2 2 3 2
## [50329] 1 1 3 3 1 2 1 3 4 3 1 2 2 3 2 2 3 1 3 1 2 1 3 3 3 1 2 2 2 1 3 1 4 3 2 3
## [50365] 4 2 2 3 3 3 1 3 2 1 2 3 3 1 4 3 3 2 2 3 4 3 1 1 2 2 2 1 2 4 3 3 2 1 2 3
## [50401] 1 1 1 3 1 3 3 2 4 4 4 1 1 3 2 2 2 3 3 1 2 3 1 3 4 1 2 2 2 1 2 3 3 1 1 1
## [50437] 3 3 1 3 2 2 1 3 1 3 1 1 3 2 3 1 3 3 2 1 3 1 3 3 3 1 1 3 2 2 3 3 3 1 3 2
## [50473] 4 3 3 3 2 1 2 2 4 3 3 2 2 4 2 3 4 4 3 1 3 2 3 3 3 3 4 2 3 3 2 3 3 3 4 3
## [50509] 4 4 1 3 3 1 3 3 3 1 2 3 1 4 3 2 2 1 2 3 3 3 3 4 4 3 3 3 2 4 3 3 2 3 4 4
## [50545] 4 1 3 3 2 2 1 2 2 2 2 3 3 3 2 2 2 3 1 3 2 4 3 1 3 2 3 4 3 2 1 4 3 1 4 3
## [50581] 1 4 3 2 3 3 3 1 1 4 3 3 3 3 2 2 3 1 1 2 3 3 3 4 3 1 3 1 3 2 3 3 2 3 2 4
## [50617] 1 3 1 3 3 1 3 1 2 4 3 3 1 1 1 3 4 3 1 4 1 2 1 4 3 3 3 1 2 3 3 2 3 2 1 1
## [50653] 1 3 1 3 3 3 3 2 1 2 4 2 2 2 2 1 3 4 2 3 1 1 3 1 1 3 2 3 3 1 3 1 4 3 3 3
## [50689] 3 1 3 1 1 2 2 3 3 3 3 2 2 3 3 3 2 4 2 3 4 3 3 2 1 4 2 4 3 3 1 2 1 1 4 1
## [50725] 2 3 3 3 2 1 1 4 3 3 4 1 3 2 3 4 1 2 3 3 1 4 1 2 1 4 3 2 4 1 2 1 4 2 3 3
## [50761] 3 2 3 1 3 3 2 3 3 2 1 4 1 3 4 3 1 4 3 3 3 3 2 2 3 2 2 4 2 3 2 2 2 3 2 2
## [50797] 4 3 1 3 4 1 1 4 2 2 3 3 2 4 4 1 2 2 3 2 1 2 3 4 1 2 3 3 2 1 2 3 3 4 4 2
## [50833] 3 2 3 3 3 1 2 4 4 1 1 3 3 4 3 3 3 1 2 1 2 3 1 3 2 3 1 1 2 2 1 1 2 3 3 3
## [50869] 4 4 2 3 1 3 4 1 3 3 2 3 2 2 1 3 2 3 1 3 1 4 3 3 3 4 3 1 4 4 3 1 3 2 1 2
## [50905] 1 2 3 3 1 3 4 3 1 4 3 2 2 4 1 3 1 1 2 2 3 3 4 3 1 3 1 2 1 2 4 1 4 2 3 1
## [50941] 3 2 3 3 4 4 3 3 2 3 2 2 3 3 2 1 3 3 4 4 2 3 2 3 3 3 2 3 1 3 3 2 1 2 1 2
## [50977] 4 3 1 3 3 1 2 3 3 3 1 1 2 1 2 1 2 1 2 3 3 1 2 3 1 4 1 3 3 3 4 4 2 3 2 2
## [51013] 4 1 3 2 3 1 2 4 2 4 1 1 1 4 3 3 1 2 4 3 3 2 3 3 4 1 2 1 2 1 4 1 2 2 3 3
## [51049] 3 2 3 3 3 1 4 3 1 1 1 2 2 2 3 3 3 2 3 2 2 1 2 3 1 2 3 4 4 2 2 1 2 2 2 1
## [51085] 2 3 3 3 3 3 3 1 2 3 3 2 3 3 1 3 1 3 4 3 1 3 1 2 2 3 1 3 3 4 2 1 3 2 1 3
## [51121] 4 3 3 3 1 3 2 3 1 4 1 1 1 1 1 3 2 4 3 2 3 3 2 3 3 3 4 1 3 3 2 3 2 3 3 3
## [51157] 2 3 2 1 2 1 1 3 3 3 1 2 4 1 1 3 3 3 3 2 1 3 2 3 3 2 2 2 1 2 1 3 3 3 1 3
## [51193] 1 4 3 3 4 3 2 3 3 3 1 4 1 3 3 1 3 1 1 3 2 3 1 1 1 4 3 2 3 2 2 1 3 2 3 3
## [51229] 2 1 1 2 2 2 2 4 1 1 3 3 3 2 2 3 3 1 2 2 4 2 2 4 1 3 3 3 3 3 3 4 2 2 3 1
## [51265] 3 1 4 4 4 2 3 1 3 1 2 4 3 3 3 1 4 4 2 2 3 3 3 3 4 3 1 2 1 4 1 3 3 2 3 3
## [51301] 1 1 3 3 1 2 1 2 3 3 4 2 3 3 2 3 2 3 4 4 4 3 3 2 4 1 1 2 1 1 3 1 4 4 3 4
## [51337] 2 4 3 1 1 3 3 2 2 1 4 3 2 1 3 1 1 1 2 4 1 1 1 2 1 2 2 4 3 3 3 3 3 3 1 1
## [51373] 2 1 3 1 4 2 1 3 4 3 2 1 1 3 3 2 1 2 2 1 3 3 3 4 3 3 4 3 4 3 3 2 3 3 1 2
## [51409] 2 3 2 2 3 2 1 1 3 2 3 3 2 3 3 3 2 4 1 2 3 3 2 1 2 3 3 4 1 3 1 3 2 3 2 1
## [51445] 3 2 1 3 3 3 3 3 2 3 4 3 4 2 3 3 3 1 4 2 1 1 2 4 1 3 3 2 2 1 3 1 4 3 2 3
## [51481] 1 3 3 2 3 3 2 2 3 1 1 3 3 1 2 1 2 3 1 3 3 3 1 3 4 2 2 1 3 3 3 2 3 2 3 4
## [51517] 3 1 3 1 4 4 2 2 2 3 2 4 3 1 2 1 1 3 1 1 2 2 3 1 2 2 4 2 3 2 3 3 1 2 1 1
## [51553] 3 3 3 3 2 3 1 2 2 3 2 3 3 1 3 3 3 3 3 4 1 3 2 2 2 3 4 1 2 2 3 4 2 3 3 3
## [51589] 3 1 2 3 3 1 1 2 3 1 2 1 1 3 2 3 3 1 1 2 3 2 3 3 3 3 1 3 2 2 2 1 4 4 3 1
## [51625] 3 3 3 1 2 1 3 3 1 1 4 1 2 2 4 2 1 3 2 2 3 4 2 2 1 1 3 3 1 2 1 1 4 2 4 1
## [51661] 4 3 4 2 3 2 2 2 2 2 3 4 4 3 4 3 1 4 3 2 4 3 3 3 2 3 1 3 3 3 2 4 1 3 3 3
## [51697] 3 3 1 1 3 4 3 3 3 3 3 1 3 1 2 1 3 2 3 2 1 2 2 3 3 1 3 1 1 3 3 3 3 3 4 2
## [51733] 3 3 1 4 2 4 1 3 3 2 1 3 2 3 1 2 3 3 2 3 1 2 1 3 2 1 3 1 2 3 3 3 3 2 1 2
## [51769] 1 2 3 3 1 4 1 3 4 1 3 1 3 1 3 1 2 4 3 3 3 1 3 3 3 3 4 1 2 2 2 2 4 3 3 2
## [51805] 1 1 1 3 2 2 2 3 2 3 1 3 3 3 3 2 3 3 2 3 1 1 3 2 1 2 1 3 2 1 3 3 3 3 4 2
## [51841] 1 2 3 4 4 3 4 3 3 3 1 2 1 3 2 2 1 3 1 1 4 3 1 2 4 3 1 3 3 2 3 3 4 1 3 4
## [51877] 3 4 2 1 4 3 1 3 3 1 3 3 3 4 1 2 3 3 3 4 1 2 4 2 3 2 3 3 3 3 3 3 3 4 3 1
## [51913] 3 3 1 3 3 3 1 2 2 4 3 1 2 4 3 3 1 3 1 1 1 2 1 2 1 4 3 1 3 2 3 3 1 1 2 1
## [51949] 3 2 1 1 4 2 4 1 4 3 2 2 1 1 1 1 4 4 3 3 4 3 1 4 3 4 4 3 2 3 1 3 2 2 2 4
## [51985] 1 3 2 3 2 2 2 1 3 2 1 1 1 4 3 2 4 3 3 3 4 3 3 2 3 2 1 4 3 2 2 2 2 3 4 3
## [52021] 2 1 1 2 4 1 3 4 4 3 3 2 4 3 3 3 2 1 3 1 1 3 2 3 4 4 3 2 2 3 1 1 4 1 1 2
## [52057] 3 1 4 3 2 2 1 2 1 1 3 3 1 2 1 4 2 3 3 3 2 4 3 4 3 3 1 4 4 2 3 2 3 1 2 1
## [52093] 3 3 3 2 3 3 3 2 1 3 2 4 1 2 2 1 3 4 4 4 2 1 2 3 1 2 3 3 1 2 3 2 2 3 3 1
## [52129] 1 2 2 1 1 2 3 3 3 3 3 3 2 3 2 3 1 2 3 1 3 3 3 4 2 3 3 4 2 2 2 3 1 1 1 3
## [52165] 1 3 3 2 3 3 1 4 1 4 3 2 1 4 2 3 2 2 2 3 3 3 1 1 3 2 3 1 2 1 3 2 4 4 4 2
## [52201] 3 4 2 3 1 3 4 3 3 1 3 1 3 1 2 2 2 4 2 4 4 2 4 3 4 2 1 3 2 3 3 3 1 2 2 4
## [52237] 2 3 1 1 4 3 2 3 3 3 3 3 2 3 1 2 3 4 3 4 2 3 1 4 2 1 3 3 3 2 3 1 4 4 1 3
## [52273] 3 3 1 2 3 1 3 2 4 1 3 4 1 3 4 3 1 2 3 4 3 2 3 3 4 2 4 2 1 3 2 3 3 2 4 2
## [52309] 4 3 4 3 3 3 4 3 2 2 2 1 1 4 2 2 1 3 2 2 4 3 4 4 2 2 2 4 3 1 2 2 3 3 4 2
## [52345] 3 1 3 4 2 1 2 3 3 4 3 2 3 1 3 2 2 3 2 3 4 3 3 2 4 2 3 1 2 2 3 2 1 2 3 2
## [52381] 3 3 1 2 3 3 4 1 3 2 2 2 2 1 1 2 3 1 3 4 3 2 3 3 1 3 2 4 3 1 2 3 1 2 3 3
## [52417] 3 1 4 2 2 3 1 4 2 4 2 3 1 4 3 3 1 1 3 4 1 2 1 2 3 3 1 4 1 1 3 2 1 2 1 4
## [52453] 2 3 4 2 3 3 1 2 3 3 2 1 1 3 4 3 2 3 3 3 1 3 4 1 2 3 2 3 3 2 1 1 2 2 2 1
## [52489] 1 2 1 1 1 2 4 2 2 3 2 4 3 4 2 3 2 3 4 1 2 3 3 2 2 3 2 2 3 2 3 3 1 1 4 3
## [52525] 3 3 3 3 1 3 4 1 2 3 1 4 1 1 3 3 1 1 4 3 3 3 3 4 3 4 2 2 1 3 3 3 1 2 3 1
## [52561] 2 1 1 2 4 3 2 1 1 2 2 1 1 3 2 3 1 3 2 3 3 1 4 4 2 4 1 2 1 2 1 3 3 4 1 1
## [52597] 1 3 2 4 3 3 3 2 3 3 1 3 4 3 3 1 3 3 2 3 4 2 2 4 3 3 2 3 1 3 3 3 3 4 3 4
## [52633] 3 3 1 1 3 2 4 3 3 2 1 3 3 4 4 1 1 3 1 2 1 1 1 3 2 3 1 3 2 1 3 3 1 3 2 4
## [52669] 1 4 1 3 1 4 1 3 2 1 2 2 3 3 1 4 2 4 2 1 4 3 2 4 2 1 3 2 3 3 1 3 1 3 2 3
## [52705] 4 1 3 1 1 2 3 3 2 1 2 3 2 3 4 3 1 3 2 1 1 2 1 1 2 1 1 1 1 3 3 3 2 3 3 1
## [52741] 2 4 4 2 3 1 3 1 3 2 2 1 3 2 4 3 3 3 1 3 1 3 3 3 2 4 3 3 4 2 3 4 2 3 3 1
## [52777] 1 3 2 3 2 2 3 3 2 2 2 3 2 1 1 1 2 2 2 3 2 4 4 2 2 3 1 2 1 3 3 4 3 3 3 3
## [52813] 2 3 2 1 1 1 3 1 1 1 1 3 1 1 1 3 2 3 2 3 2 4 1 3 3 2 1 2 4 3 2 3 2 3 4 4
## [52849] 2 2 2 1 1 2 1 2 2 2 3 4 1 1 2 3 2 2 3 1 1 1 4 1 1 3 2 1 4 1 3 1 3 3 1 4
## [52885] 4 2 3 2 2 2 3 3 1 3 3 3 2 1 4 3 1 3 4 3 2 1 3 3 1 1 1 2 3 3 2 3 3 2 1 1
## [52921] 2 3 3 3 2 2 4 4 1 3 1 3 3 2 1 2 1 3 4 1 2 2 3 4 2 2 4 2 4 4 4 4 4 3 3 2
## [52957] 4 1 2 3 1 4 1 4 3 1 3 2 2 2 3 3 3 1 2 3 3 1 3 3 2 2 3 4 2 4 3 3 3 4 1 2
## [52993] 1 3 3 3 1 1 2 2 2 1 3 3 2 3 2 2 1 3 4 3 1 3 3 3 3 4 2 2 2 2 4 1 4 3 2 3
## [53029] 2 3 3 3 2 1 2 4 3 3 2 3 3 4 1 3 4 1 4 4 3 1 1 2 1 3 2 2 2 2 3 3 2 1 2 4
## [53065] 2 3 1 2 3 2 3 4 1 3 3 3 3 2 4 1 3 3 3 4 4 4 4 4 1 2 1 3 1 2 4 2 3 4 2 1
## [53101] 3 3 2 3 4 3 3 3 3 1 2 3 4 3 2 1 3 3 2 1 1 2 3 4 1 1 3 4 2 1 3 3 3 3 3 4
## [53137] 3 2 3 1 2 3 1 4 3 3 4 1 4 3 2 3 2 3 1 3 2 3 2 1 2 3 3 3 2 3 3 3 3 1 2 3
## [53173] 4 2 1 3 4 1 3 2 3 2 4 3 1 2 1 4 3 2 1 1 2 1 3 3 1 3 3 2 4 3 2 4 3 2 3 1
## [53209] 3 1 4 3 4 1 3 2 2 2 4 3 3 3 3 1 3 3 2 3 3 2 2 2 1 2 3 3 3 1 3 3 1 3 3 2
## [53245] 3 3 3 3 2 4 1 1 1 1 3 3 3 4 4 3 3 3 3 2 3 2 3 3 2 2 1 1 2 2 2 2 3 1 3 3
## [53281] 4 3 2 2 3 2 3 1 1 2 3 2 3 3 2 2 2 4 4 2 2 3 3 3 4 1 3 3 1 1 1 2 2 1 1 2
## [53317] 3 4 3 3 2 3 1 1 3 1 3 1 2 3 1 4 3 1 3 1 1 3 2 3 2 4 2 2 2 2 3 2 3 4 1 1
## [53353] 3 2 3 1 4 4 1 1 3 1 3 1 3 3 3 4 1 2 2 1 3 2 1 2 3 1 1 1 1 1 1 3 1 2 2 2
## [53389] 1 3 3 3 2 3 1 2 2 2 2 3 2 3 1 3 1 1 4 1 4 2 3 2 3 3 2 4 2 2 2 3 2 3 4 3
## [53425] 2 1 2 4 2 3 2 1 2 3 1 3 1 3 3 2 2 3 4 3 3 3 1 1 3 4 4 2 3 2 3 2 4 1 3 4
## [53461] 3 3 3 3 2 1 2 2 3 1 2 2 4 3 2 1 2 2 4 2 4 4 3 2 2 3 3 1 3 2 3 3 3 2 3 3
## [53497] 3 1 2 1 3 4 3 3 2 1 3 2 3 3 3 1 2 3 1 2 2 3 3 4 3 2 3 3 1 3 2 2 4 4 3 2
## [53533] 1 2 3 4 2 2 3 3 1 3 3 3 3 3 2 2 3 2 4 3 1 2 2 2 1 3 3 3 3 3 4 4 2 1 3 1
## [53569] 3 1 3 1 2 1 1 2 1 2 3 3 4 1 1 1 3 4 1 2 3 3 2 1 2 4 1 1 3 4 4 3 1 1 2 3
## [53605] 1 2 2 3 2 2 3 2 1 3 3 2 2 1 1 4 3 1 2 3 2 2 3 4 1 2 2 3 3 3 2 1 3 3 2 2
## [53641] 3 2 3 1 4 2 4 3 3 2 4 3 3 4 4 3 1 3 2 3 1 3 2 1 2 3 3 3 3 3 2 3 4 2 2 1
## [53677] 3 4 2 1 3 1 3 3 1 3 2 3 2 3 3 1 1 3 2 1 2 4 3 2 3 1 2 3 2 4 3 2 3 1 2 3
## [53713] 1 1 3 2 3 2 2 2 3 3 4 3 3 2 2 1 2 1 3 3 2 1 3 1 3 1 2 3 2 1 1 3 3 3 2 3
## [53749] 1 3 3 1 1 2 2 3 2 4 4 3 1 1 3 4 2 3 2 1 4 2 4 3 2 4 4 2 1 1 1 1 2 4 3 1
## [53785] 2 2 1 4 1 2 2 4 3 3 4 1 1 1 3 3 2 2 3 2 3 2 2 1 3 4 2 1 1 3 3 2 2 3 2 4
## [53821] 1 2 4 3 3 3 2 4 3 2 4 3 3 2 3 4 2 1 4 3 3 3 4 2 2 3 3 1 1 1 3 3 3 2 2 2
## [53857] 4 3 3 1 1 3 4 4 2 3 1 3 1 4 4 2 4 3 1 3 3 1 4 3 1 4 3 1 1 3 3 4 2 1 2 3
## [53893] 2 1 1 3 4 2 1 1 3 3 2 3 1 2 2 3 1 2 2 3 1 1 1 3 1 3 3 1 4 3 2 2 3 1 3 2
## [53929] 3 2 1 2 2 2 1 3 3 4 1 4 1 4 1 1 3 3 1 2 2 1 1 4 1 1 3 3 2 3 1 2 1 3 1 2
## [53965] 1 1 3 3 2 3 2 2 4 4 4 1 1 2 3 4 2 1 3 2 2 1 1 1 1 3 2 3 3 3 3 2 3 2 1 3
## [54001] 1 2 3 1 2 3 3 1 2 3 4 3 1 3 1 2 3 4 3 2 2 1 2 2 1 3 1 3 3 3 1 4 1 2 2 4
## [54037] 2 3 1 2 3 3 3 3 3 1 1 2 3 4 1 3 3 1 3 2 1 3 1 3 3 2 2 2 3 3 2 1 4 4 1 3
## [54073] 3 3 1 1 1 1 3 3 1 2 3 3 4 3 3 1 3 1 3 1 4 3 1 4 3 4 2 1 4 2 3 4 3 1 3 2
## [54109] 3 3 3 3 2 1 2 3 2 2 3 3 3 1 3 2 1 2 1 3 4 2 3 3 3 1 4 4 3 2 2 1 1 2 2 2
## [54145] 2 3 3 2 3 1 2 3 1 2 2 4 3 3 1 3 4 2 2 2 3 2 2 2 3 2 3 3 3 3 2 4 2 2 2 4
## [54181] 3 3 1 3 4 3 4 2 1 2 3 1 3 2 2 4 3 3 3 3 2 2 4 1 3 4 3 1 1 3 1 3 1 3 2 2
## [54217] 1 1 1 1 3 4 4 1 4 1 3 3 3 3 2 3 1 3 3 2 3 1 4 4 3 3 3 2 1 2 2 2 2 3 4 1
## [54253] 3 1 2 2 3 2 4 1 3 3 3 4 1 1 1 3 2 2 1 1 4 1 3 2 1 3 3 1 2 4 3 2 1 2 3 2
## [54289] 3 3 2 2 3 1 3 4 2 1 3 1 1 1 1 1 1 3 1 2 3 1 3 4 2 3 1 4 4 3 1 2 2 3 3 4
## [54325] 3 2 2 2 2 1 2 2 3 3 2 4 2 1 4 3 3 1 2 2 2 2 2 4 4 3 1 3 1 1 4 4 3 2 2 2
## [54361] 1 2 3 1 3 3 2 2 2 2 3 3 1 3 3 1 1 3 1 2 2 3 4 3 1 1 4 3 1 4 2 1 4 2 2 4
## [54397] 3 2 1 3 2 3 4 1 3 4 2 2 3 2 2 3 1 1 4 3 3 4 1 3 1 4 3 2 2 4 1 3 3 1 4 2
## [54433] 2 3 3 3 3 3 1 1 3 2 4 3 1 1 1 1 1 1 3 4 1 1 1 1 4 3 2 3 1 3 2 3 3 3 3 1
## [54469] 3 3 4 1 3 2 3 4 3 1 3 3 1 1 3 4 2 4 3 3 4 1 2 3 2 2 2 2 2 3 3 3 3 1 2 2
## [54505] 2 3 3 3 1 3 2 2 2 2 3 2 3 3 2 3 3 2 3 3 2 2 1 2 4 2 1 1 3 1 3 3 3 3 1 1
## [54541] 3 3 3 2 3 4 3 1 1 3 3 3 3 3 3 1 1 2 3 1 2 4 2 3 3 2 3 3 2 3 2 2 2 1 3 1
## [54577] 3 3 3 1 3 1 3 2 4 4 3 3 3 2 1 1 2 1 3 3 2 1 3 1 4 1 3 1 2 2 3 1 1 1 2 1
## [54613] 3 4 3 2 4 1 3 1 1 2 3 4 3 2 3 3 3 2 2 3 3 2 1 2 2 3 1 3 2 2 1 1 3 1 1 3
## [54649] 3 2 2 2 3 3 3 3 2 2 3 3 2 3 1 4 1 4 3 1 3 3 3 3 1 2 4 3 1 3 3 3 2 3 4 3
## [54685] 3 1 2 1 3 1 1 1 1 4 1 3 3 3 2 2 2 3 3 1 2 2 4 3 2 4 4 4 4 2 3 3 2 4 3 3
## [54721] 4 1 4 3 1 3 3 3 2 4 4 3 3 3 2 2 1 3 3 3 1 2 4 1 3 4 1 1 4 4 2 4 3 3 1 3
## [54757] 1 3 3 3 3 1 4 4 3 1 1 3 3 1 4 1 2 1 1 3 1 3 3 1 4 3 2 1 4 1 3 2 3 1 1 3
## [54793] 4 1 4 3 3 1 2 2 3 3 2 1 3 1 3 1 3 3 3 2 1 3 2 3 1 1 3 1 3 4 3 1 4 2 2 1
## [54829] 1 4 3 4 1 2 3 2 2 3 1 4 1 1 3 3 1 3 3 3 2 1 2 3 2 2 3 1 3 1 3 3 3 2 3 2
## [54865] 1 3 2 3 4 3 3 1 2 3 3 3 2 2 4 3 3 1 1 1 1 1 3 1 2 3 3 3 3 2 2 2 3 3 4 1
## [54901] 3 2 3 3 2 3 3 3 4 3 2 3 3 3 2 3 1 2 3 2 2 3 1 3 1 3 1 3 2 2 2 2 4 3 3 3
## [54937] 4 3 3 3 2 3 2 3 2 1 3 3 2 2 2 2 2 1 3 3 1 2 3 3 3 1 2 4 2 3 2 1 4 2 4 3
## [54973] 2 3 1 3 2 3 2 2 4 2 2 4 3 3 2 2 3 4 1 3 1 1 3 4 3 1 3 3 2 3 3 2 1 3 2 3
## [55009] 2 2 1 3 3 2 3 1 3 3 1 4 1 3 2 1 3 3 3 1 3 3 4 3 1 4 4 1 4 3 2 4 2 3 3 3
## [55045] 4 1 2 3 2 3 3 3 2 1 3 1 1 2 2 3 3 3 4 4 3 1 1 2 3 2 4 2 3 3 3 3 4 3 2 2
## [55081] 2 3 1 2 3 4 2 4 2 2 2 3 1 1 2 1 3 4 4 2 4 3 1 2 1 1 3 4 1 2 2 4 2 2 2 3
## [55117] 1 4 3 2 2 3 3 1 2 2 4 1 3 1 3 3 3 2 3 2 2 1 3 4 1 3 1 3 3 1 3 2 1 3 2 1
## [55153] 3 2 1 2 1 4 3 3 2 3 2 3 2 3 3 4 3 2 4 3 2 1 4 4 3 3 2 2 4 4 3 3 3 1 3 4
## [55189] 3 4 1 3 3 3 3 2 1 4 1 4 3 2 4 1 2 2 3 2 2 1 3 3 4 2 1 4 1 1 1 1 1 3 2 4
## [55225] 2 1 3 2 3 3 1 2 3 1 3 4 1 4 2 4 3 3 3 1 2 3 1 3 3 3 3 1 4 1 1 1 4 3 3 3
## [55261] 3 3 2 1 4 1 2 1 3 4 2 3 1 3 3 2 3 4 3 2 1 4 1 2 2 3 1 3 1 2 1 2 4 2 3 2
## [55297] 4 4 2 2 2 1 3 4 3 4 1 3 1 3 2 3 1 2 4 4 3 4 2 3 2 1 3 4 3 3 3 3 1 3 3 2
## [55333] 4 4 3 4 3 2 4 2 3 2 4 4 2 3 4 2 3 2 2 2 3 2 3 3 4 1 1 2 3 3 3 1 2 2 3 1
## [55369] 2 3 1 3 1 4 1 3 3 4 4 2 1 2 4 1 3 1 4 2 2 2 3 1 3 2 4 3 1 2 2 4 1 2 1 2
## [55405] 1 2 3 3 1 4 2 3 3 4 2 3 2 2 3 1 2 1 4 3 3 1 3 1 4 3 3 3 1 2 2 1 2 3 2 4
## [55441] 4 1 2 1 3 2 3 1 1 2 3 4 3 2 2 3 3 2 1 4 1 4 2 2 2 3 1 4 3 4 1 1 2 1 3 2
## [55477] 3 1 2 2 2 3 4 3 2 3 1 3 4 2 3 2 2 2 3 4 3 4 4 3 2 3 2 3 3 1 3 2 1 3 1 2
## [55513] 3 2 2 1 2 3 2 3 2 1 2 3 3 3 3 1 3 3 2 3 2 1 3 3 2 3 4 3 1 1 2 2 3 1 1 4
## [55549] 3 2 2 4 4 3 1 4 4 4 3 3 2 4 1 4 2 3 3 2 2 1 3 1 1 3 3 1 3 3 1 1 2 4 4 1
## [55585] 2 2 2 3 3 2 3 4 1 3 3 3 2 3 3 1 3 2 2 2 3 1 2 2 3 3 2 3 3 2 1 1 3 1 1 2
## [55621] 1 1 4 2 3 4 1 3 4 3 3 4 3 3 2 1 4 1 3 3 1 1 1 1 1 3 1 2 3 3 1 1 2 1 3 1
## [55657] 1 1 4 3 2 3 2 3 1 3 4 1 4 3 3 1 1 1 3 1 3 2 2 3 1 3 3 4 3 2 3 1 3 1 2 4
## [55693] 4 3 2 2 1 1 2 1 2 4 2 3 2 2 3 3 3 1 2 2 1 4 3 3 4 3 3 1 2 3 2 3 2 3 4 4
## [55729] 1 3 3 4 1 3 2 2 2 1 2 1 2 4 4 2 3 4 2 2 1 4 4 3 3 2 4 2 3 4 3 2 3 1 2 3
## [55765] 3 1 3 3 1 4 2 2 3 3 3 1 3 3 4 3 2 2 3 1 4 3 3 4 3 3 3 2 3 1 4 2 3 3 2 2
## [55801] 3 2 1 2 3 3 3 1 3 3 4 3 1 2 3 1 1 2 3 3 3 2 3 2 2 4 3 4 2 2 3 2 3 4 2 2
## [55837] 4 3 2 2 3 3 2 3 1 2 3 3 4 1 3 3 2 3 2 3 4 1 3 3 3 4 2 1 1 2 3 3 4 2 2 1
## [55873] 4 3 2 1 2 2 3 4 3 2 1 2 1 2 3 3 3 1 3 2 3 1 2 1 3 3 2 3 3 3 1 2 3 3 1 2
## [55909] 3 1 1 1 4 2 1 2 3 2 2 1 3 2 3 3 2 1 3 1 3 1 1 2 3 2 4 3 3 2 2 1 1 2 3 3
## [55945] 3 1 2 3 1 4 4 3 2 3 3 4 2 4 1 3 3 2 3 1 3 3 1 1 1 3 1 3 3 2 1 1 2 3 3 2
## [55981] 1 3 2 1 2 2 1 1 4 1 1 4 3 3 3 3 3 1 3 4 3 3 1 3 4 3 2 3 3 2 3 4 3 1 3 4
## [56017] 4 4 2 2 1 1 1 2 3 1 3 2 3 2 1 3 1 3 4 3 3 4 3 3 1 2 1 4 2 3 1 2 1 1 2 2
## [56053] 3 3 1 2 3 1 1 1 1 2 1 3 3 3 2 4 1 1 2 3 3 3 2 4 3 1 3 4 3 3 2 3 3 4 2 3
## [56089] 3 1 2 1 2 4 2 1 4 1 2 4 3 4 4 4 2 2 3 2 3 2 3 4 3 1 3 3 4 3 2 1 1 1 2 1
## [56125] 3 3 3 1 2 1 2 2 3 1 2 3 4 2 1 1 1 1 2 2 1 1 4 3 2 2 1 3 1 1 1 4 3 2 3 2
## [56161] 2 3 3 3 3 4 1 2 3 4 3 3 3 1 4 3 3 3 3 1 3 2 2 3 3 2 3 3 1 3 2 3 4 3 2 2
## [56197] 2 2 3 2 3 1 2 3 4 4 1 2 4 1 3 4 3 1 1 2 3 2 3 3 1 1 1 3 2 3 4 2 4 2 3 3
## [56233] 3 2 3 2 3 2 4 3 3 1 1 3 2 3 2 1 4 1 4 3 2 1 3 3 2 3 3 4 3 1 1 3 2 3 1 1
## [56269] 2 3 3 1 3 2 3 2 3 3 4 3 2 2 1 1 3 3 3 3 3 3 1 2 2 4 1 2 3 2 2 3 1 3 3 1
## [56305] 2 1 3 3 2 2 4 3 3 1 3 2 2 3 2 2 4 3 4 2 3 3 3 4 2 3 3 2 3 2 2 4 2 3 1 1
## [56341] 3 1 1 3 1 3 3 1 4 1 1 2 3 4 2 1 2 4 3 1 1 2 2 4 2 1 3 3 3 3 1 1 3 3 1 1
## [56377] 2 4 3 4 1 3 3 2 3 4 4 4 4 4 4 3 3 3 2 1 3 2 2 2 1 1 3 1 3 3 3 1 4 3 4 3
## [56413] 1 1 4 2 3 1 2 2 2 3 3 3 1 2 1 4 2 2 3 3 2 3 3 2 2 3 1 2 2 4 4 3 3 4 3 3
## [56449] 2 2 1 3 2 1 4 3 3 3 3 4 3 1 1 1 4 2 2 3 3 3 3 3 3 1 3 3 1 4 3 3 2 4 1 1
## [56485] 1 2 4 2 3 1 3 2 3 3 3 2 3 4 2 2 1 3 2 3 1 2 3 2 1 2 2 3 2 1 1 3 2 2 3 1
## [56521] 1 1 2 1 3 4 1 2 1 2 2 2 1 4 3 4 3 4 3 2 2 2 3 3 1 3 4 3 2 3 2 1 1 3 1 1
## [56557] 2 2 3 3 4 1 3 1 2 3 2 3 1 4 3 3 3 2 3 4 4 3 2 3 2 3 1 2 3 2 2 1 1 3 3 3
## [56593] 2 3 2 3 3 3 1 3 3 1 1 2 1 2 4 3 3 2 1 3 2 1 1 3 1 2 1 1 1 3 3 3 3 1 3 1
## [56629] 1 2 3 3 2 1 1 3 3 1 1 3 3 1 2 2 3 3 3 3 2 3 2 1 3 3 4 3 3 4 3 3 1 3 1 3
## [56665] 3 2 1 3 3 2 3 1 4 3 3 2 1 1 3 3 1 1 3 3 1 2 3 3 2 1 3 1 2 3 2 3 4 3 3 4
## [56701] 3 3 3 3 3 4 1 1 1 2 3 3 1 3 2 3 1 3 3 4 4 3 1 1 3 2 1 4 3 3 4 3 1 3 1 3
## [56737] 3 3 4 2 2 1 3 4 3 2 1 2 3 3 1 3 3 3 4 2 4 2 4 4 3 2 1 3 3 4 1 2 1 3 3 3
## [56773] 1 2 3 3 1 1 3 2 2 2 1 4 2 3 4 2 1 2 3 3 3 4 2 1 2 3 3 1 3 3 1 3 1 1 3 3
## [56809] 1 4 1 3 4 3 4 1 1 1 2 1 4 2 4 4 4 1 1 3 3 3 3 3 3 3 3 3 4 4 2 1 2 3 1 2
## [56845] 2 2 4 1 3 3 1 2 4 3 2 1 4 1 1 2 1 1 4 1 2 2 2 2 3 3 4 1 1 1 2 2 3 1 4 3
## [56881] 2 2 1 4 1 1 1 2 4 2 3 3 1 2 2 3 4 1 2 2 1 4 1 3 1 3 3 2 2 4 1 3 4 1 3 3
## [56917] 3 4 3 2 1 3 2 4 3 2 3 3 3 3 3 3 3 3 1 2 2 1 2 1 2 2 4 1 3 3 3 4 3 1 4 1
## [56953] 3 4 1 2 3 3 2 3 2 3 2 1 4 4 1 1 4 3 3 2 3 1 2 2 1 3 3 2 3 3 1 2 2 1 1 3
## [56989] 3 3 2 2 3 3 2 3 2 2 2 1 3 3 2 1 3 1 3 4 2 2 3 1 1 3 3 3 3 3 1 2 1 3 3 3
## [57025] 3 4 1 4 2 2 1 3 2 1 1 2 1 2 2 1 3 3 3 3 1 3 1 3 3 3 1 1 1 3 3 2 3 3 1 4
## [57061] 2 3 2 1 2 1 3 2 1 1 4 3 1 1 1 1 4 4 3 1 3 1 1 3 4 2 1 3 3 2 1 4 2 2 1 2
## [57097] 3 4 2 2 1 2 1 3 2 3 4 2 4 3 1 3 3 3 2 3 3 2 3 2 1 3 2 3 3 3 1 4 2 1 3 4
## [57133] 2 4 2 3 3 3 2 2 4 2 3 1 2 1 2 3 1 2 3 4 1 2 1 4 2 3 1 2 1 3 1 3 2 3 3 3
## [57169] 1 1 4 3 2 2 4 1 3 4 2 2 1 1 1 4 1 1 3 2 1 3 3 3 2 3 2 3 4 4 4 2 1 1 2 1
## [57205] 2 4 3 3 4 2 3 4 4 2 3 3 1 3 3 2 1 1 2 4 3 4 1 1 4 3 3 4 4 1 1 2 2 1 1 3
## [57241] 3 4 3 3 2 1 4 2 3 1 1 2 2 2 3 3 1 1 3 3 2 4 3 4 2 3 2 3 3 1 4 3 3 2 3 1
## [57277] 1 2 2 3 3 2 1 3 3 1 2 3 2 3 4 3 1 3 1 3 3 4 3 4 3 3 3 2 3 2 4 3 3 3 2 1
## [57313] 3 4 3 3 2 2 3 3 2 3 3 3 2 1 3 3 1 4 2 3 3 2 3 1 1 1 1 2 1 3 2 1 3 3 2 3
## [57349] 3 3 1 2 2 3 1 1 4 3 1 3 4 2 4 2 3 3 1 2 2 1 3 2 3 3 3 3 1 1 4 3 3 3 3 2
## [57385] 4 3 1 4 3 1 2 2 2 1 1 3 3 3 3 3 3 3 2 4 3 3 4 4 3 2 1 1 3 3 4 1 3 3 4 1
## [57421] 1 3 1 3 3 3 3 4 1 3 4 1 1 3 2 3 1 2 3 4 1 1 2 2 3 3 4 4 2 1 2 2 2 3 3 1
## [57457] 4 2 2 3 2 4 3 1 2 3 1 1 4 3 1 1 2 3 1 1 2 3 3 3 2 2 3 1 4 3 2 1 2 3 3 2
## [57493] 4 2 3 3 2 2 3 1 3 3 3 3 2 3 3 1 3 4 3 3 4 3 2 3 1 3 4 2 1 3 3 2 2 4 4 2
## [57529] 1 2 2 2 1 4 3 1 2 3 3 3 3 4 3 1 3 3 1 2 4 3 4 1 3 3 4 2 2 4 2 2 1 4 3 2
## [57565] 3 2 2 4 3 2 1 3 4 3 3 3 2 1 4 4 3 1 2 3 3 3 1 4 2 3 1 3 2 3 1 2 3 3 3 2
## [57601] 1 2 3 1 3 1 1 3 3 1 4 3 3 1 4 1 3 1 2 2 3 1 1 3 1 2 3 1 1 2 1 1 2 1 2 3
## [57637] 3 2 3 1 2 2 1 3 2 2 4 2 3 4 1 3 3 4 3 2 3 2 4 4 3 1 1 1 2 1 3 4 2 1 1 4
## [57673] 2 2 4 3 3 1 2 1 4 3 4 3 2 3 3 2 3 3 3 3 3 2 3 4 3 2 2 2 2 4 3 2 4 1 3 3
## [57709] 1 3 4 4 4 2 3 3 2 3 1 2 3 3 3 1 3 2 3 1 3 3 1 3 3 1 3 4 3 3 2 3 4 2 2 3
## [57745] 3 3 1 3 3 1 3 3 2 3 2 4 2 1 2 1 1 1 1 3 2 1 3 3 2 3 3 1 1 3 4 1 3 3 1 3
## [57781] 2 4 4 3 2 2 1 2 2 3 3 1 4 3 3 2 3 2 3 2 3 2 3 1 3 2 3 1 3 3 4 1 1 3 4 4
## [57817] 2 3 1 1 4 4 3 3 3 2 2 1 3 3 3 3 3 2 3 3 3 3 2 3 4 3 1 3 2 2 3 1 2 3 2 2
## [57853] 3 1 1 3 1 3 1 3 3 1 3 3 1 2 4 3 1 3 2 1 1 2 2 1 2 4 3 4 3 1 2 1 3 1 2 3
## [57889] 2 3 3 1 3 3 2 3 2 3 4 1 2 2 1 3 2 3 2 2 1 3 3 1 1 3 1 3 2 3 2 3 3 1 2 2
## [57925] 2 1 2 3 3 4 1 4 3 2 2 2 1 3 1 3 1 3 1 1 2 1 3 1 2 2 4 1 3 4 2 1 4 3 3 4
## [57961] 3 3 3 2 2 2 3 2 4 3 4 2 2 3 2 3 2 3 4 3 2 1 4 2 2 3 1 4 3 1 3 3 2 4 1 1
## [57997] 3 3 2 3 4 2 4 3 2 2 1 2 2 2 3 2 3 1 3 1 1 4 1 1 3 4 4 2 1 2 3 2 4 2 2 1
## [58033] 3 3 2 3 4 1 1 2 1 3 1 4 2 1 3 2 1 2 3 3 1 4 3 4 2 4 2 1 1 4 1 3 3 4 3 4
## [58069] 1 2 3 2 3 2 2 4 4 4 1 1 2 4 1 2 4 1 2 2 3 3 4 3 3 3 4 4 3 3 2 3 3 2 3 3
## [58105] 3 1 2 2 1 2 2 4 1 2 2 3 1 2 4 4 2 1 3 2 3 2 3 2 3 2 4 3 2 3 2 3 3 4 2 3
## [58141] 1 2 3 2 2 1 1 2 2 3 3 3 3 3 1 4 2 3 1 3 1 4 3 3 2 3 2 1 3 1 3 2 1 2 1 3
## [58177] 1 2 2 1 4 3 3 3 2 4 2 1 1 1 1 1 2 1 1 1 2 4 1 3 4 3 2 3 4 2 1 3 2 1 3 3
## [58213] 1 3 2 2 3 1 3 2 3 3 2 4 4 1 4 2 1 3 3 1 1 2 3 4 3 4 4 1 3 1 4 4 3 4 3 2
## [58249] 3 3 1 4 3 3 1 2 4 3 3 2 3 4 3 3 1 2 4 1 2 1 2 4 2 1 3 3 2 4 2 1 3 3 3 2
## [58285] 1 3 4 3 2 3 2 2 2 2 3 1 3 1 2 2 2 1 3 4 1 2 2 4 2 3 4 1 2 2 2 1 2 2 2 4
## [58321] 2 3 1 2 2 3 1 2 1 1 2 3 3 1 2 2 3 2 3 4 1 1 3 2 4 1 3 2 2 4 3 1 2 4 3 3
## [58357] 3 2 1 2 1 2 3 3 3 3 2 1 2 3 1 4 3 4 3 2 3 1 1 2 1 2 2 2 2 1 2 4 4 2 4 2
## [58393] 4 1 3 1 1 3 3 3 1 1 4 2 3 1 3 3 1 4 3 2 1 1 3 3 3 3 3 1 1 2 4 3 2 1 3 1
## [58429] 3 1 3 2 3 4 2 3 2 2 4 2 1 1 4 1 3 1 2 2 3 3 3 3 2 2 3 3 2 3 3 3 1 4 4 1
## [58465] 2 2 2 4 3 2 3 3 4 3 1 1 1 1 3 2 4 3 1 3 1 3 1 2 2 1 3 2 3 3 3 2 4 3 1 1
## [58501] 4 4 3 2 1 3 2 3 1 4 4 3 3 1 3 3 1 3 4 1 1 3 3 3 2 2 3 3 1 1 2 2 1 1 2 4
## [58537] 3 1 4 1 3 2 1 3 2 3 1 1 3 1 1 4 3 1 2 3 2 3 1 2 2 1 3 3 2 1 3 3 4 2 2 1
## [58573] 1 3 4 1 3 1 1 1 3 1 2 3 2 2 4 3 1 3 3 3
##
## Within cluster sum of squares by cluster:
## [1] 54522.16 50894.19 131879.84 42310.57
## (between_SS / total_SS = 60.2 %)
##
## Available components:
##
## [1] "cluster" "centers" "totss" "withinss" "tot.withinss"
## [6] "betweenss" "size" "iter" "ifault"
# Visualize clustering results (using PCA to reduce to 2D for visualization)
pca_result <- prcomp(scaled_data, center = TRUE, scale. = TRUE)
pca_data <- data.frame(pca_result$x[,1:2], cluster = as.factor(kmeans_result$cluster))
ggplot(pca_data, aes(x = PC1, y = PC2, color = cluster)) +
geom_point() +
labs(title = "K-means Clustering (PCA Reduced)", x = "Principal Component 1", y = "Principal Component 2") +
theme_minimal()
# Add clustering results to the original data
car_data2$cluster <- kmeans_result$cluster
# Analyze feature distribution for each cluster
cluster_summary <- car_data2 %>%
group_by(cluster) %>%
summarise_all(mean, na.rm = TRUE)
## Warning: There were 112 warnings in `summarise()`.
## The first warning was:
## ℹ In argument: `policy_id = (function (x, ...) ...`.
## ℹ In group 1: `cluster = 1`.
## Caused by warning in `mean.default()`:
## ! argument is not numeric or logical: returning NA
## ℹ Run `dplyr::last_dplyr_warnings()` to see the 111 remaining warnings.
print(cluster_summary)
## # A tibble: 4 × 42
## cluster policy_id subscription_length vehicle_age customer_age region_code
## <int> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 NA 6.81 1.78 44.8 NA
## 2 2 NA 4.40 0.486 45.4 NA
## 3 3 NA 6.72 1.70 44.9 NA
## 4 4 NA 6.46 1.56 43.4 NA
## # ℹ 36 more variables: region_density <dbl>, segment <dbl>, model <dbl>,
## # fuel_type <dbl>, max_torque <dbl>, max_power <dbl>, engine_type <dbl>,
## # airbags <dbl>, is_esc <dbl>, is_adjustable_steering <dbl>, is_tpms <dbl>,
## # is_parking_sensors <dbl>, is_parking_camera <dbl>, rear_brakes_type <dbl>,
## # displacement <dbl>, cylinder <dbl>, transmission_type <dbl>,
## # steering_type <dbl>, turning_radius <dbl>, length <dbl>, width <dbl>,
## # gross_weight <dbl>, is_front_fog_lights <dbl>, …
# Analyze insurance claim rate for each cluster
cluster_claim_analysis <- car_data2 %>%
group_by(cluster) %>%
summarise(
claim_rate = mean(claim_status)
)
print(cluster_claim_analysis)
## # A tibble: 4 × 2
## cluster claim_rate
## <int> <dbl>
## 1 1 0.0643
## 2 2 0.0611
## 3 3 0.0678
## 4 4 0.0580
# Read data
car_data2 <- read.csv("~/Downloads/car_data2.csv")
# List of numerical features
numeric_features <- c(
'subscription_length', 'vehicle_age', 'customer_age', 'region_density',
'airbags', 'displacement', 'cylinder', 'turning_radius', 'length', 'width',
'gross_weight', 'ncap_rating'
)
# Extract numerical feature data
numeric_data <- car_data2 %>%
select(all_of(numeric_features))
# Add target variable
numeric_data$claim_status <- car_data2$claim_status
# Calculate correlation matrix
cor_matrix <- cor(numeric_data, use = "complete.obs")
# Plot correlation heatmap using corrplot package
corrplot(cor_matrix, method = "color", type = "upper",
tl.col = "black", tl.srt = 45,
addCoef.col = "black", number.cex = 0.7)
# Plot correlation heatmap using ggcorrplot package
ggcorrplot(cor_matrix,
method = "square",
lab = TRUE,
lab_size = 3,
colors = c("blue", "white", "red"),
title = "Correlation Heatmap",
tl.cex = 12,
tl.srt = 45)
# Create a list of box plots
plots <- lapply(numeric_features, function(feature) {
ggplot(car_data2, aes_string(y = feature)) +
geom_boxplot() +
labs(title = feature) +
theme(axis.text.x = element_blank(), axis.ticks.x = element_blank())
})
# Arrange box plots side by side
grid.arrange(grobs = plots, ncol = 4)
# List of numerical features
numeric_features <- c(
'subscription_length', 'vehicle_age', 'customer_age', 'region_density',
'airbags', 'displacement', 'cylinder', 'turning_radius', 'length', 'width',
'gross_weight', 'ncap_rating'
)
# Extract numerical feature data
numeric_data <- car_data2 %>%
select(all_of(numeric_features))
# Standardize data
numeric_data_scaled <- scale(numeric_data)
# Perform PCA analysis
pca_result <- prcomp(numeric_data_scaled, center = TRUE, scale. = TRUE)
# Print PCA results
summary(pca_result)
## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## Standard deviation 2.5680 1.07877 1.01215 0.97761 0.87817 0.84039 0.68139
## Proportion of Variance 0.5496 0.09698 0.08537 0.07964 0.06427 0.05885 0.03869
## Cumulative Proportion 0.5496 0.64655 0.73192 0.81156 0.87583 0.93468 0.97337
## PC8 PC9 PC10 PC11 PC12
## Standard deviation 0.41389 0.32143 0.1896 0.08923 0.03152
## Proportion of Variance 0.01428 0.00861 0.0030 0.00066 0.00008
## Cumulative Proportion 0.98765 0.99626 0.9992 0.99992 1.00000
# Convert claim_status to a factor variable
car_data2$claim_status <- as.factor(car_data2$claim_status)
# Visualize PCA results
# Principal Component plot
fviz_pca_ind(pca_result,
geom.ind = "point", # Show points for individuals
pointshape = 21,
pointsize = 2,
fill.ind = car_data2$claim_status, # Color by claim status
palette = c("#00AFBB", "#FC4E07"),
addEllipses = TRUE, # Add confidence ellipses
label = "var",
col.var = "black",
repel = TRUE) +
theme_minimal()
# Variable plot
fviz_pca_var(pca_result,
col.var = "contrib", # Color by contribution
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE) +
theme_minimal()
# List of numerical features
numeric_features <- c(
'subscription_length', 'vehicle_age', 'customer_age', 'region_density',
'airbags', 'displacement', 'cylinder', 'turning_radius', 'length', 'width',
'gross_weight', 'ncap_rating'
)
# Extract numerical feature data
numeric_data <- car_data2 %>%
select(all_of(numeric_features))
# Remove duplicate rows
numeric_data <- numeric_data %>%
distinct()
# Standardize numerical features
numeric_data_scaled <- scale(numeric_data)
# Set random seed to ensure reproducibility
set.seed(123)
# Perform t-SNE analysis
tsne_result <- Rtsne(numeric_data_scaled, dims = 2, perplexity = 30, verbose = TRUE, max_iter = 500)
## Performing PCA
## Read the 56436 x 12 data matrix successfully!
## Using no_dims = 2, perplexity = 30.000000, and theta = 0.500000
## Computing input similarities...
## Building tree...
## - point 10000 of 56436
## - point 20000 of 56436
## - point 30000 of 56436
## - point 40000 of 56436
## - point 50000 of 56436
## Done in 2.87 seconds (sparsity = 0.001952)!
## Learning embedding...
## Iteration 50: error is 119.521453 (50 iterations in 4.83 seconds)
## Iteration 100: error is 119.521435 (50 iterations in 5.13 seconds)
## Iteration 150: error is 116.560211 (50 iterations in 6.45 seconds)
## Iteration 200: error is 100.191522 (50 iterations in 4.96 seconds)
## Iteration 250: error is 94.107682 (50 iterations in 4.86 seconds)
## Iteration 300: error is 4.462061 (50 iterations in 4.74 seconds)
## Iteration 350: error is 4.037850 (50 iterations in 4.68 seconds)
## Iteration 400: error is 3.750858 (50 iterations in 4.87 seconds)
## Iteration 450: error is 3.531928 (50 iterations in 5.24 seconds)
## Iteration 500: error is 3.355857 (50 iterations in 4.90 seconds)
## Fitting performed in 50.66 seconds.
# Extract t-SNE results
tsne_data <- as.data.frame(tsne_result$Y)
colnames(tsne_data) <- c("Dim1", "Dim2")
# Merge t-SNE results with the claim_status from the original data
tsne_data <- cbind(tsne_data, claim_status = car_data2$claim_status[1:nrow(tsne_data)])
# Convert claim_status to a factor variable
tsne_data$claim_status <- as.factor(tsne_data$claim_status)
# Visualize t-SNE results
ggplot(tsne_data, aes(x = Dim1, y = Dim2, color = claim_status)) +
geom_point(alpha = 0.7) +
labs(title = "t-SNE Analysis of Vehicle Data", x = "Dimension 1", y = "Dimension 2") +
scale_color_manual(values = c("0" = "#00AFBB", "1" = "#FC4E07")) +
theme_minimal()
# Set random seed to ensure reproducibility
set.seed(123)
# Perform K-means clustering on the t-SNE results
kmeans_result <- kmeans(tsne_data[, c("Dim1", "Dim2")], centers = 5) # Assuming 5 clusters
# Add clustering results to the data
tsne_data$cluster <- as.factor(kmeans_result$cluster)
# Visualize K-means clustering results
ggplot(tsne_data, aes(x = Dim1, y = Dim2, color = cluster)) +
geom_point(alpha = 0.7) +
labs(title = "t-SNE and K-means Clustering of Vehicle Data", x = "Dimension 1", y = "Dimension 2") +
theme_minimal()
# Load necessary libraries
library(cluster)
library(dendextend)
library(ggplot2)
# Set random seed to ensure reproducibility
set.seed(123)
# Perform random sampling on the t-SNE results
sample_indices <- sample(1:nrow(tsne_data), size = 10000)
tsne_sample <- tsne_data[sample_indices, ]
# Perform hierarchical clustering on the t-SNE sample
dist_matrix <- dist(tsne_sample[, c("Dim1", "Dim2")])
hc_result <- hclust(dist_matrix, method = "ward.D2")
# Convert to dendrogram object and remove labels
dend <- as.dendrogram(hc_result)
dend <- dend %>% set("labels", NULL) # Remove labels
## Warning in `labels<-.dendrogram`(dend, value = value, ...): The lengths of the
## new labels is shorter than the number of leaves in the dendrogram - labels are
## recycled.
## Warning in rep(new_labels, length.out = leaves_length): 'x' is NULL so the
## result will be NULL
# Plot dendrogram
plot(dend, main = "Dendrogram of t-SNE Sample Results")
# Cut the dendrogram at different levels and visualize the results
# Assume we want to observe 3 different levels (2 clusters, 3 clusters, and 5 clusters)
k_values <- c(2, 3, 5)
colors <- c("red", "blue", "green", "orange", "purple")
for (k in k_values) {
# Cut the dendrogram
clusters <- cutree(hc_result, k = k)
tsne_sample$cluster <- as.factor(clusters)
# Visualize clustering results
p <- ggplot(tsne_sample, aes(x = Dim1, y = Dim2, color = cluster)) +
geom_point(alpha = 0.7) +
labs(title = paste("t-SNE and Hierarchical Clustering with", k, "Clusters"),
x = "Dimension 1", y = "Dimension 2") +
scale_color_manual(values = colors[1:k]) +
theme_minimal()
print(p)
}
# Load necessary libraries
library(cluster)
library(dendextend)
library(ggplot2)
library(dplyr)
# Set random seed to ensure reproducibility
set.seed(123)
# Perform random sampling on the t-SNE results
sample_indices <- sample(1:nrow(tsne_data), size = 10000)
tsne_sample <- tsne_data[sample_indices, ]
# Perform hierarchical clustering on the t-SNE sample
dist_matrix <- dist(tsne_sample[, c("Dim1", "Dim2")])
hc_result <- hclust(dist_matrix, method = "ward.D2")
# Convert to dendrogram object and remove labels
dend <- as.dendrogram(hc_result)
dend <- dend %>% set("labels", NULL) # Remove labels
## Warning in `labels<-.dendrogram`(dend, value = value, ...): The lengths of the
## new labels is shorter than the number of leaves in the dendrogram - labels are
## recycled.
## Warning in rep(new_labels, length.out = leaves_length): 'x' is NULL so the
## result will be NULL
# Plot dendrogram
plot(dend, main = "Dendrogram of t-SNE Sample Results")
# Cut the dendrogram at different levels and visualize the results
# Assume we want to observe 3 different levels (2 clusters, 3 clusters, and 5 clusters)
k_values <- c(2, 3, 5)
colors <- c("red", "blue", "green", "orange", "purple")
for (k in k_values) {
# Cut the dendrogram
clusters <- cutree(hc_result, k = k)
tsne_sample$cluster <- as.factor(clusters)
# Calculate the proportion of each cluster
cluster_proportions <- prop.table(table(tsne_sample$cluster))
print(paste("Proportions of clusters for k =", k))
print(cluster_proportions)
# Merge cluster information with the original data
merged_data <- cbind(tsne_sample, car_data2[sample_indices, numeric_features])
# Summarize characteristics of each cluster
cluster_summary <- merged_data %>%
group_by(cluster) %>%
summarise_all(mean, na.rm = TRUE)
print(paste("Cluster characteristics for k =", k))
print(cluster_summary)
# Visualize clustering results
p <- ggplot(tsne_sample, aes(x = Dim1, y = Dim2, color = cluster)) +
geom_point(alpha = 0.7) +
labs(title = paste("t-SNE and Hierarchical Clustering with", k, "Clusters"),
x = "Dimension 1", y = "Dimension 2") +
scale_color_manual(values = colors[1:k]) +
theme_minimal()
print(p)
}
## [1] "Proportions of clusters for k = 2"
##
## 1 2
## 0.509 0.491
## Warning: There were 2 warnings in `summarise()`.
## The first warning was:
## ℹ In argument: `claim_status = (function (x, ...) ...`.
## ℹ In group 1: `cluster = 1`.
## Caused by warning in `mean.default()`:
## ! argument is not numeric or logical: returning NA
## ℹ Run `dplyr::last_dplyr_warnings()` to see the 1 remaining warning.
## [1] "Cluster characteristics for k = 2"
## # A tibble: 2 × 16
## cluster Dim1 Dim2 claim_status subscription_length vehicle_age customer_age
## <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 -7.56 0.331 NA 6.15 1.40 44.8
## 2 2 7.80 -0.310 NA 6.09 1.38 44.9
## # ℹ 9 more variables: region_density <dbl>, airbags <dbl>, displacement <dbl>,
## # cylinder <dbl>, turning_radius <dbl>, length <dbl>, width <dbl>,
## # gross_weight <dbl>, ncap_rating <dbl>
## [1] "Proportions of clusters for k = 3"
##
## 1 2 3
## 0.2412 0.4910 0.2678
## Warning: There were 3 warnings in `summarise()`.
## The first warning was:
## ℹ In argument: `claim_status = (function (x, ...) ...`.
## ℹ In group 1: `cluster = 1`.
## Caused by warning in `mean.default()`:
## ! argument is not numeric or logical: returning NA
## ℹ Run `dplyr::last_dplyr_warnings()` to see the 2 remaining warnings.
## [1] "Cluster characteristics for k = 3"
## # A tibble: 3 × 16
## cluster Dim1 Dim2 claim_status subscription_length vehicle_age customer_age
## <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 -7.62 -9.77 NA 6.10 1.43 44.8
## 2 2 7.80 -0.310 NA 6.09 1.38 44.9
## 3 3 -7.51 9.43 NA 6.19 1.38 44.8
## # ℹ 9 more variables: region_density <dbl>, airbags <dbl>, displacement <dbl>,
## # cylinder <dbl>, turning_radius <dbl>, length <dbl>, width <dbl>,
## # gross_weight <dbl>, ncap_rating <dbl>
## [1] "Proportions of clusters for k = 5"
##
## 1 2 3 4 5
## 0.2412 0.3052 0.1212 0.1466 0.1858
## Warning: There were 5 warnings in `summarise()`.
## The first warning was:
## ℹ In argument: `claim_status = (function (x, ...) ...`.
## ℹ In group 1: `cluster = 1`.
## Caused by warning in `mean.default()`:
## ! argument is not numeric or logical: returning NA
## ℹ Run `dplyr::last_dplyr_warnings()` to see the 4 remaining warnings.
## [1] "Cluster characteristics for k = 5"
## # A tibble: 5 × 16
## cluster Dim1 Dim2 claim_status subscription_length vehicle_age customer_age
## <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 -7.62 -9.77 NA 6.10 1.43 44.8
## 2 2 5.11 -4.16 NA 6.16 1.38 44.8
## 3 3 -1.59 14.0 NA 6.22 1.36 44.8
## 4 4 -12.4 5.65 NA 6.16 1.39 44.8
## 5 5 12.2 6.01 NA 5.99 1.38 45.1
## # ℹ 9 more variables: region_density <dbl>, airbags <dbl>, displacement <dbl>,
## # cylinder <dbl>, turning_radius <dbl>, length <dbl>, width <dbl>,
## # gross_weight <dbl>, ncap_rating <dbl>